Split (1)

train · 975k rows

modelId string	author string	last_modified timestamp[us, tz=UTC]	downloads int64	likes int64	library_name string	tags list	pipeline_tag string	createdAt timestamp[us, tz=UTC]	card string
anarasgarli/blockassist-bc-fast_howling_cockroach_1756067699	anarasgarli	2025-08-24T20:35:42Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "fast howling cockroach", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:35:29Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - fast howling cockroach --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kimweb3/blockassist-bc-camouflaged_sedate_pheasant_1756067701	kimweb3	2025-08-24T20:35:27Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "camouflaged sedate pheasant", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:35:23Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - camouflaged sedate pheasant --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
sdfsdgsgdf/blockassist-bc-barky_snorting_dingo_1756067155	sdfsdgsgdf	2025-08-24T20:35:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "barky snorting dingo", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:35:19Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - barky snorting dingo --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756067400	kapalbalap	2025-08-24T20:30:58Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:30:52Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kavpro/blockassist-bc-tall_lively_caribou_1756067360	kavpro	2025-08-24T20:30:22Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "tall lively caribou", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:30:09Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - tall lively caribou --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kimweb3/blockassist-bc-camouflaged_sedate_pheasant_1756067395	kimweb3	2025-08-24T20:30:18Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "camouflaged sedate pheasant", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:30:14Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - camouflaged sedate pheasant --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
0xaoyama/blockassist-bc-muscular_zealous_gorilla_1756067206	0xaoyama	2025-08-24T20:27:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "muscular zealous gorilla", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:27:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - muscular zealous gorilla --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
sampingkaca72/blockassist-bc-armored_stealthy_elephant_1756065372	sampingkaca72	2025-08-24T20:25:24Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "armored stealthy elephant", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:25:20Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - armored stealthy elephant --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
adity12345/Roberta_coaid	adity12345	2025-08-24T20:23:49Z	0	0	transformers	[ "transformers", "tensorboard", "safetensors", "roberta", "text-classification", "generated_from_trainer", "base_model:adity12345/Roberta_covert", "base_model:finetune:adity12345/Roberta_covert", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-08-24T20:23:39Z	--- library_name: transformers license: mit base_model: adity12345/Roberta_covert tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: Roberta_coaid results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Roberta_coaid This model is a fine-tuned version of [adity12345/Roberta_covert](https://huggingface.co/adity12345/Roberta_covert) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2850 - Accuracy: 0.897 - Auc: 0.862 - Precision: 0.905 - Recall: 0.984 - F1: 0.943 - F1-macro: 0.721 - F1-micro: 0.897 - F1-weighted: 0.881 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| Auc \| Precision \| Recall \| F1 \| F1-macro \| F1-micro \| F1-weighted \| \|:-------------:\|:------:\|:----:\|:---------------:\|:--------:\|:-----:\|:---------:\|:------:\|:-----:\|:--------:\|:--------:\|:-----------:\| \| 1.1024 \| 1.0638 \| 50 \| 0.2850 \| 0.897 \| 0.862 \| 0.905 \| 0.984 \| 0.943 \| 0.721 \| 0.897 \| 0.881 \| ### Framework versions - Transformers 4.55.2 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756066265	IvanJAjebu	2025-08-24T20:12:21Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "thorny slender capybara", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:12:12Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - thorny slender capybara --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
0xaoyama/blockassist-bc-muscular_zealous_gorilla_1756065997	0xaoyama	2025-08-24T20:07:05Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "muscular zealous gorilla", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:07:00Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - muscular zealous gorilla --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
asteroid999/blockassist-bc-furry_smooth_caterpillar_1756065649	asteroid999	2025-08-24T20:01:40Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "furry smooth caterpillar", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T20:01:36Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - furry smooth caterpillar --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
marcuscedricridia/arc-Q4_K_M-GGUF	marcuscedricridia	2025-08-24T20:01:14Z	0	0	transformers	[ "transformers", "gguf", "text-generation-inference", "unsloth", "qwen3", "llama-cpp", "gguf-my-repo", "en", "base_model:NewstaR/arc", "base_model:quantized:NewstaR/arc", "license:apache-2.0", "endpoints_compatible", "region:us" ]	null	2025-08-24T20:01:08Z	--- base_model: NewstaR/arc tags: - text-generation-inference - transformers - unsloth - qwen3 - llama-cpp - gguf-my-repo license: apache-2.0 language: - en --- # marcuscedricridia/arc-Q4_K_M-GGUF This model was converted to GGUF format from [`NewstaR/arc`](https://huggingface.co/NewstaR/arc) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. Refer to the [original model card](https://huggingface.co/NewstaR/arc) for more details on the model. ## Use with llama.cpp Install llama.cpp through brew (works on Mac and Linux) ```bash brew install llama.cpp ``` Invoke the llama.cpp server or the CLI. ### CLI: ```bash llama-cli --hf-repo marcuscedricridia/arc-Q4_K_M-GGUF --hf-file arc-q4_k_m.gguf -p "The meaning to life and the universe is" ``` ### Server: ```bash llama-server --hf-repo marcuscedricridia/arc-Q4_K_M-GGUF --hf-file arc-q4_k_m.gguf -c 2048 ``` Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. Step 1: Clone llama.cpp from GitHub. ``` git clone https://github.com/ggerganov/llama.cpp ``` Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). ``` cd llama.cpp && LLAMA_CURL=1 make ``` Step 3: Run inference through the main binary. ``` ./llama-cli --hf-repo marcuscedricridia/arc-Q4_K_M-GGUF --hf-file arc-q4_k_m.gguf -p "The meaning to life and the universe is" ``` or ``` ./llama-server --hf-repo marcuscedricridia/arc-Q4_K_M-GGUF --hf-file arc-q4_k_m.gguf -c 2048 ```
VIDEOS-afrin-viral-video-Orginal-link-xk/New.full.videos.afrin.apu.Viral.Video.Official.Tutorial	VIDEOS-afrin-viral-video-Orginal-link-xk	2025-08-24T19:58:30Z	0	0	null	[ "region:us" ]	null	2025-08-24T19:56:08Z	[🌐 CLICK HERE 🟢==►► WATCH NOW](https://videohere.top/) [🔴 CLICK HERE 🌐==►► Download Now)](https://videohere.top/) [<img alt="fsd" src="https://i.postimg.cc/qvPp49Sm/ythngythg.gif">](https://videohere.top/)
kapalbalap/blockassist-bc-peaceful_wary_owl_1756065446	kapalbalap	2025-08-24T19:58:28Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:58:16Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Vasya777/blockassist-bc-lumbering_enormous_sloth_1756065454	Vasya777	2025-08-24T19:58:24Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lumbering enormous sloth", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:58:06Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lumbering enormous sloth --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
mradermacher/sign-language-20250823-190451-GGUF	mradermacher	2025-08-24T19:53:35Z	0	0	transformers	[ "transformers", "gguf", "autotrain", "text-generation-inference", "text-generation", "peft", "en", "dataset:devparagiri/dataset-sign-language-20250823-190451", "base_model:devparagiri/sign-language-20250823-190451", "base_model:quantized:devparagiri/sign-language-20250823-190451", "license:other", "endpoints_compatible", "region:us", "conversational" ]	text-generation	2025-08-24T18:55:46Z	--- base_model: devparagiri/sign-language-20250823-190451 datasets: - devparagiri/dataset-sign-language-20250823-190451 language: - en library_name: transformers license: other mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - autotrain - text-generation-inference - text-generation - peft --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/devparagiri/sign-language-20250823-190451 <!-- provided-files --> *For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#sign-language-20250823-190451-GGUF).* weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion. ## Usage If you are unsure how to use GGUF files, refer to one of [TheBloke's READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for more details, including on how to concatenate multi-part files. ## Provided Quants (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants) \| Link \| Type \| Size/GB \| Notes \| \|:-----\|:-----\|--------:\|:------\| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q2_K.gguf) \| Q2_K \| 1.5 \| \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q3_K_S.gguf) \| Q3_K_S \| 1.8 \| \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q3_K_M.gguf) \| Q3_K_M \| 2.1 \| lower quality \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.IQ4_XS.gguf) \| IQ4_XS \| 2.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q3_K_L.gguf) \| Q3_K_L \| 2.2 \| \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q4_K_S.gguf) \| Q4_K_S \| 2.3 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q4_K_M.gguf) \| Q4_K_M \| 2.5 \| fast, recommended \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q5_K_S.gguf) \| Q5_K_S \| 2.7 \| \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q5_K_M.gguf) \| Q5_K_M \| 2.9 \| \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q6_K.gguf) \| Q6_K \| 3.2 \| very good quality \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.Q8_0.gguf) \| Q8_0 \| 4.2 \| fast, best quality \| \| [GGUF](https://huggingface.co/mradermacher/sign-language-20250823-190451-GGUF/resolve/main/sign-language-20250823-190451.f16.gguf) \| f16 \| 7.7 \| 16 bpw, overkill \| Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better): ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png) And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9 ## FAQ / Model Request See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized. ## Thanks I thank my company, [nethype GmbH](https://www.nethype.de/), for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. <!-- end -->
kapalbalap/blockassist-bc-peaceful_wary_owl_1756065116	kapalbalap	2025-08-24T19:52:53Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:52:47Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756064958	ggozzy	2025-08-24T19:50:33Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:50:25Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
katanyasekolah/blockassist-bc-silky_sprightly_cassowary_1756063170	katanyasekolah	2025-08-24T19:49:00Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "silky sprightly cassowary", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:48:43Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - silky sprightly cassowary --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
mohda/blockassist-bc-regal_fierce_hummingbird_1756064378	mohda	2025-08-24T19:40:27Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "regal fierce hummingbird", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:40:20Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - regal fierce hummingbird --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
coelacanthxyz/blockassist-bc-finicky_thriving_grouse_1756062664	coelacanthxyz	2025-08-24T19:38:46Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "finicky thriving grouse", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:38:40Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - finicky thriving grouse --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
adity12345/Roberta_covidFact	adity12345	2025-08-24T19:36:38Z	0	0	transformers	[ "transformers", "tensorboard", "safetensors", "xlm-roberta", "text-classification", "generated_from_trainer", "base_model:FacebookAI/xlm-roberta-base", "base_model:finetune:FacebookAI/xlm-roberta-base", "license:mit", "autotrain_compatible", "endpoints_compatible", "region:us" ]	text-classification	2025-08-24T19:36:21Z	--- library_name: transformers license: mit base_model: FacebookAI/xlm-roberta-base tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: Roberta_covidFact results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # Roberta_covidFact This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.6179 - Accuracy: 0.694 - Auc: 0.498 - Precision: 0.0 - Recall: 0.0 - F1: 0.0 - F1-macro: 0.41 - F1-micro: 0.694 - F1-weighted: 0.569 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 2 - mixed_precision_training: Native AMP ### Training results \| Training Loss \| Epoch \| Step \| Validation Loss \| Accuracy \| Auc \| Precision \| Recall \| F1 \| F1-macro \| F1-micro \| F1-weighted \| \|:-------------:\|:------:\|:----:\|:---------------:\|:--------:\|:-----:\|:---------:\|:------:\|:---:\|:--------:\|:--------:\|:-----------:\| \| 0.6882 \| 0.5587 \| 50 \| 0.6186 \| 0.694 \| 0.504 \| 0.0 \| 0.0 \| 0.0 \| 0.41 \| 0.694 \| 0.569 \| \| 0.633 \| 1.1117 \| 100 \| 0.6167 \| 0.694 \| 0.524 \| 0.0 \| 0.0 \| 0.0 \| 0.41 \| 0.694 \| 0.569 \| \| 0.6282 \| 1.6704 \| 150 \| 0.6179 \| 0.694 \| 0.498 \| 0.0 \| 0.0 \| 0.0 \| 0.41 \| 0.694 \| 0.569 \| ### Framework versions - Transformers 4.55.2 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.21.4
koloni/blockassist-bc-deadly_graceful_stingray_1756062601	koloni	2025-08-24T19:35:44Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "deadly graceful stingray", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:35:40Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - deadly graceful stingray --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Vasya777/blockassist-bc-lumbering_enormous_sloth_1756063684	Vasya777	2025-08-24T19:32:48Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lumbering enormous sloth", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:28:37Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lumbering enormous sloth --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756063763	ggozzy	2025-08-24T19:30:35Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:30:29Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756063747	kapalbalap	2025-08-24T19:30:02Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:29:57Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
maxibillion1975/blockassist-bc-iridescent_squeaky_sandpiper_1756061935	maxibillion1975	2025-08-24T19:23:27Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "iridescent squeaky sandpiper", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:23:24Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - iridescent squeaky sandpiper --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756063045	ggozzy	2025-08-24T19:18:35Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:18:29Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756063014	kapalbalap	2025-08-24T19:17:53Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:17:47Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
zenqqq/blockassist-bc-restless_reptilian_caterpillar_1756062906	zenqqq	2025-08-24T19:16:24Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "restless reptilian caterpillar", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:16:15Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - restless reptilian caterpillar --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Delnith/Sugoi-14B-Ultra-HF-gptqmodel-8bit	Delnith	2025-08-24T19:14:54Z	0	1	null	[ "safetensors", "qwen2", "text-generation", "conversational", "en", "ja", "dataset:lmg-anon/VNTL-v3.1-1k", "base_model:sugoitoolkit/Sugoi-14B-Ultra-HF", "base_model:quantized:sugoitoolkit/Sugoi-14B-Ultra-HF", "license:apache-2.0", "8-bit", "gptq", "region:us" ]	text-generation	2025-08-24T19:06:49Z	--- license: apache-2.0 datasets: - lmg-anon/VNTL-v3.1-1k language: - en - ja base_model: - sugoitoolkit/Sugoi-14B-Ultra-HF pipeline_tag: text-generation --- # Sugoi LLM 14B Ultra (HF version) This is an 8-bit version of Sugoi 14B Ultra, quantized using GPTQmodel and the VNTL-v3.1-1k dataset. This quant should work better than GGUF for certain backends like vLLM and aphrodite-engine, which excel at asynchronous prompting. Unleashing the full potential of the previous sugoi 14B model, Sugoi 14B Ultra delivers near-double translation accuracy compared to its quantized predecessor—achieving a BLEU score of 21.38 vs 13.67. Its prompt-following skills rival those of Qwen 2.5 Base, especially when handling the bracket-heavy text commonly found in RPG Maker projects. --- ## Model Overview - Key Improvements * Nearly 2× BLEU score boost over previous quantized version (21.38 vs 13.67). * Stronger prompt adherence, especially with RPGM-style bracketed text. - Ideal Use Cases * Japanese → English translation—especially for game dialogue or RPG text. * Interactive environments—works well with chat UIs like LM Studio. --- ## System Prompt & Settings Must include a system prompt for best performance: > You are a professional localizer whose primary goal is to translate Japanese to English. You should use colloquial or slang or nsfw vocabulary if it makes the translation more accurate. Always respond in English. Additional recommendations: - Context length: ~10 lines (too much may degrade quality). - In LM Studio, you can interactively ask grammar or context questions, or switch target language via the prompt (quality may vary). --- ## Experimental Features These features are experimental and may need tuning: 1. Tool Integration & JSON Output 2. RPGM Tag Preservation --- ## Recommended Sampling Parameters \| Parameter \| Value \| \|-----------------\|--------\| \| Temperature \| 0.1 \| \| Top-K \| 40 \| \| Top-P \| 0.95 \| \| Min-P \| 0.05 \| \| Repeat Penalty \| 1.1 \| --- ## Evaluation & Comparison - Quantitative: BLEU score doubled vs prior version (21.38 vs 13.67). - Qualitative: Effective with prompt complexity and RPG Maker markup—delivers clean and accurate translations. --- ## Limitations & Usage Notes - Overly long context may “poison” the output—keep it around 10 lines for best results. - Experimental features like JSON formatting and tag preservation may not always work perfectly—review outputs carefully. - Performance may vary depending on the prompt complexity and UI/tool environment. - Only uncensored for translation task with translation system prompt, other use case such as roleplay,chat may still trigger qwen censoring. --- ## Getting the Model Available via Files and Versions tab above.
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756062806	ggozzy	2025-08-24T19:14:37Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:14:31Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Vasya777/blockassist-bc-lumbering_enormous_sloth_1756062516	Vasya777	2025-08-24T19:14:05Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lumbering enormous sloth", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:09:11Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lumbering enormous sloth --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
tokenizers-chat-templates-only/Mistral-Nemo-Instruct-2407	tokenizers-chat-templates-only	2025-08-24T19:12:27Z	0	0	null	[ "license:apache-2.0", "region:us" ]	null	2025-08-24T19:12:05Z	--- license: apache-2.0 ---
kapalbalap/blockassist-bc-peaceful_wary_owl_1756062677	kapalbalap	2025-08-24T19:12:14Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:12:08Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Khaljr/blockassist-bc-bellowing_squinting_finch_1756062688	Khaljr	2025-08-24T19:11:51Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "bellowing squinting finch", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:11:48Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - bellowing squinting finch --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
nightmedia/Kimi-VL-A3B-Thinking-2506-q6-hi-mlx	nightmedia	2025-08-24T19:09:20Z	0	0	mlx	[ "mlx", "safetensors", "kimi_vl", "text-generation", "conversational", "custom_code", "base_model:moonshotai/Kimi-VL-A3B-Thinking-2506", "base_model:quantized:moonshotai/Kimi-VL-A3B-Thinking-2506", "license:mit", "6-bit", "region:us" ]	text-generation	2025-08-24T14:02:41Z	--- base_model: moonshotai/Kimi-VL-A3B-Thinking-2506 license: mit pipeline_tag: text-generation library_name: mlx tags: - mlx --- # Kimi-VL-A3B-Thinking-2506-q6-hi-mlx This model [Kimi-VL-A3B-Thinking-2506-q6-hi-mlx](https://huggingface.co/Kimi-VL-A3B-Thinking-2506-q6-hi-mlx) was converted to MLX format from [moonshotai/Kimi-VL-A3B-Thinking-2506](https://huggingface.co/moonshotai/Kimi-VL-A3B-Thinking-2506) using mlx-lm version 0.26.3. ## Use with mlx ```bash pip install mlx-lm ``` ```python from mlx_lm import load, generate model, tokenizer = load("Kimi-VL-A3B-Thinking-2506-q6-hi-mlx") prompt = "hello" if tokenizer.chat_template is not None: messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) response = generate(model, tokenizer, prompt=prompt, verbose=True) ```
asdfsdfsdf545/blockassist-bc-restless_poisonous_orangutan_1756061580	asdfsdfsdf545	2025-08-24T19:04:41Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "restless poisonous orangutan", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T19:04:34Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - restless poisonous orangutan --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Vasya777/blockassist-bc-lumbering_enormous_sloth_1756061928	Vasya777	2025-08-24T18:59:39Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lumbering enormous sloth", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:59:20Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lumbering enormous sloth --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756061371	ggozzy	2025-08-24T18:50:42Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:50:37Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756061132	ggozzy	2025-08-24T18:46:43Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:46:37Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ALEXEY1ko/blockassist-bc-knobby_arctic_viper_1756061062	ALEXEY1ko	2025-08-24T18:45:01Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "knobby arctic viper", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:44:54Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - knobby arctic viper --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Mano-Official-Viral-Video-Clip/New.full.videos.Mano.Viral.Video.Official.Tutorial	Mano-Official-Viral-Video-Clip	2025-08-24T18:32:13Z	0	0	null	[ "region:us" ]	null	2025-08-24T18:31:55Z	<animated-image data-catalyst=""><a href="https://tinyurl.com/3ckkv2u7?Viral-Video-Original-Link" rel="nofollow" data-target="animated-image.originalLink"><img src="https://static.wixstatic.com/media/b249f9_adac8f70fb3f45b88691696c77de18f3~mv2.gif" alt="Foo" data-canonical-src="https://static.wixstatic.com/media/b249f9_adac8f70fb3f45b88691696c77de18f3~mv2.gif" style="max-width: 100%; display: inline-block;" data-target="animated-image.originalImage"></a>
adgafhsdfhdf/blockassist-bc-furry_strong_duck_1756059639	adgafhsdfhdf	2025-08-24T18:30:58Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "furry strong duck", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:30:52Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - furry strong duck --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Dassem/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf	Dassem	2025-08-24T18:28:26Z	102	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "generated_from_trainer", "rl-swarm", "grpo", "gensyn", "I am endangered gregarious wolf", "unsloth", "trl", "genrl-swarm", "I am endangered_gregarious_wolf", "conversational", "arxiv:2402.03300", "base_model:Gensyn/Qwen2.5-1.5B-Instruct", "base_model:quantized:Gensyn/Qwen2.5-1.5B-Instruct", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "4-bit", "bitsandbytes", "region:us" ]	text-generation	2025-05-03T10:52:54Z	--- base_model: Gensyn/Qwen2.5-1.5B-Instruct library_name: transformers model_name: Qwen2.5-1.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf tags: - generated_from_trainer - rl-swarm - grpo - gensyn - I am endangered gregarious wolf - unsloth - trl - genrl-swarm - I am endangered_gregarious_wolf licence: license --- # Model Card for Qwen2.5-1.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf This model is a fine-tuned version of [Gensyn/Qwen2.5-1.5B-Instruct](https://huggingface.co/Gensyn/Qwen2.5-1.5B-Instruct). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="Dassem/Qwen2.5-1.5B-Instruct-Gensyn-Swarm-endangered_gregarious_wolf", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300). ### Framework versions - TRL: 0.15.2 - Transformers: 4.51.3 - Pytorch: 2.5.1 - Datasets: 3.6.0 - Tokenizers: 0.21.1 ## Citations Cite GRPO as: ```bibtex @article{zhihong2024deepseekmath, title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}}, author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo}, year = 2024, eprint = {arXiv:2402.03300}, } ``` Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```
indoempatnol/blockassist-bc-fishy_wary_swan_1756058415	indoempatnol	2025-08-24T18:27:56Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "fishy wary swan", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:27:52Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - fishy wary swan --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756059886	kapalbalap	2025-08-24T18:25:45Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:25:38Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756059715	kapalbalap	2025-08-24T18:22:51Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:22:45Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756059285	kapalbalap	2025-08-24T18:15:28Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T18:15:22Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Orginal-haider-shah-videos-viral-35-second/LINK.haider.shah.Viral.Video.Official.Tutorial	Orginal-haider-shah-videos-viral-35-second	2025-08-24T18:06:12Z	0	0	null	[ "region:us" ]	null	2025-08-24T18:06:01Z	<animated-image data-catalyst=""><a href="https://newmovietv.online/leaked-video/?leaked-videos/" rel="nofollow" data-target="animated-image.originalLink"><img src="https://static.wixstatic.com/media/b249f9_adac8f70fb3f45b88691696c77de18f3~mv2.gif" alt="Foo" data-canonical-src="https://static.wixstatic.com/media/b249f9_adac8f70fb3f45b88691696c77de18f3~mv2.gif" style="max-width: 100%; display: inline-block;" data-target="animated-image.originalImage"></a>
lowelldiaz/blockassist-bc-prowling_feathered_stork_1756056882	lowelldiaz	2025-08-24T17:37:21Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "prowling feathered stork", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:37:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - prowling feathered stork --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
afsagag/t5-song-feature-generator	afsagag	2025-08-24T17:36:27Z	0	0	transformers	[ "transformers", "safetensors", "t5", "text2text-generation", "arxiv:1910.09700", "text-generation-inference", "endpoints_compatible", "region:us" ]	null	2025-08-24T17:36:11Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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kapalbalap/blockassist-bc-peaceful_wary_owl_1756056733	kapalbalap	2025-08-24T17:33:10Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:33:04Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Sayemahsjn/blockassist-bc-playful_feline_octopus_1756055549	Sayemahsjn	2025-08-24T17:31:34Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "playful feline octopus", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:31:30Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - playful feline octopus --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
koloni/blockassist-bc-deadly_graceful_stingray_1756055031	koloni	2025-08-24T17:29:36Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "deadly graceful stingray", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:29:33Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - deadly graceful stingray --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
gabrieln2h/Qwen3-0.6B-Gensyn-Swarm-hibernating_dextrous_chimpanzee	gabrieln2h	2025-08-24T17:24:49Z	0	0	transformers	[ "transformers", "safetensors", "qwen3", "text-generation", "rl-swarm", "genrl-swarm", "grpo", "gensyn", "I am hibernating_dextrous_chimpanzee", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-08-24T07:15:51Z	--- library_name: transformers tags: - rl-swarm - genrl-swarm - grpo - gensyn - I am hibernating_dextrous_chimpanzee --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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coelacanthxyz/blockassist-bc-finicky_thriving_grouse_1756054501	coelacanthxyz	2025-08-24T17:23:12Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "finicky thriving grouse", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:23:06Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - finicky thriving grouse --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
liukevin666/blockassist-bc-yawning_striped_cassowary_1756056096	liukevin666	2025-08-24T17:22:54Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "yawning striped cassowary", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:22:35Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - yawning striped cassowary --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
unitova/blockassist-bc-zealous_sneaky_raven_1756054524	unitova	2025-08-24T17:22:40Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "zealous sneaky raven", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:22:37Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - zealous sneaky raven --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
g-assismoraes/Qwen3-4B-Base-fpi-alpha1.6-var-assin2	g-assismoraes	2025-08-24T17:20:10Z	8	0	transformers	[ "transformers", "safetensors", "qwen3", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-08-13T01:13:43Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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calegpedia/blockassist-bc-stealthy_slimy_rooster_1756054345	calegpedia	2025-08-24T17:18:06Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stealthy slimy rooster", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:18:03Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stealthy slimy rooster --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
thyYu2024/qwen2-7b-instruct-trl-sft-newnew	thyYu2024	2025-08-24T17:16:35Z	0	0	transformers	[ "transformers", "safetensors", "generated_from_trainer", "trl", "sft", "base_model:Qwen/Qwen2-VL-7B-Instruct", "base_model:finetune:Qwen/Qwen2-VL-7B-Instruct", "endpoints_compatible", "region:us" ]	null	2025-08-24T08:56:52Z	--- base_model: Qwen/Qwen2-VL-7B-Instruct library_name: transformers model_name: qwen2-7b-instruct-trl-sft-newnew tags: - generated_from_trainer - trl - sft licence: license --- # Model Card for qwen2-7b-instruct-trl-sft-newnew This model is a fine-tuned version of [Qwen/Qwen2-VL-7B-Instruct](https://huggingface.co/Qwen/Qwen2-VL-7B-Instruct). It has been trained using [TRL](https://github.com/huggingface/trl). ## Quick start ```python from transformers import pipeline question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" generator = pipeline("text-generation", model="thyYu2024/qwen2-7b-instruct-trl-sft-newnew", device="cuda") output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] print(output["generated_text"]) ``` ## Training procedure [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/ruoxue2-stony-brook-university/qwen2vl-sft-mydataset/runs/zqe1i5ho) This model was trained with SFT. ### Framework versions - TRL: 0.20.0 - Transformers: 4.55.2 - Pytorch: 2.4.1+cu121 - Datasets: 4.0.0 - Tokenizers: 0.21.4 ## Citations Cite TRL as: ```bibtex @misc{vonwerra2022trl, title = {{TRL: Transformer Reinforcement Learning}}, author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec}, year = 2020, journal = {GitHub repository}, publisher = {GitHub}, howpublished = {\url{https://github.com/huggingface/trl}} } ```
g-assismoraes/Qwen3-4B-Base-fpi-alpha1.6-var-imdb	g-assismoraes	2025-08-24T17:16:22Z	0	0	transformers	[ "transformers", "safetensors", "qwen3", "text-generation", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-08-24T17:13:07Z	--- library_name: transformers tags: [] --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
MomlessTomato/hanamaru-kunikida	MomlessTomato	2025-08-24T17:11:39Z	25	0	diffusers	[ "diffusers", "text-to-image", "stable-diffusion", "lora", "template:sd-lora", "base_model:cagliostrolab/animagine-xl-3.0", "base_model:adapter:cagliostrolab/animagine-xl-3.0", "license:mit", "region:us" ]	text-to-image	2024-09-02T03:32:11Z	--- tags: - text-to-image - stable-diffusion - lora - diffusers - template:sd-lora widget: - text: >- high quality, defined pupil, looking at viewer, rounded pupil, defined iris, (soft iris:1.2), torso shadow, long hair, bangs, mole, hairclip, parameters: negative_prompt: >- bad_anatomy, deformation, amputation, deformity, deformed_nipples, duplicated_torso, deformed_torso, long_torso, large_torso, unproportioned_torso, (deformed_pussy:1.2), (deformed_hands:1.2), unproportioned_eyes, unproportioned_head, small_head, duplicated_nose, big_nose, fusioned_clothes, fusioned_arms, undefined_limbs, divided_pussy, red_pussy, duplicated_pussy, deformed_anus, deformed_pussy, output: url: images/3.png base_model: Linaqruf/animagine-xl-3.0 instance_prompt: id_hanamaru_kunikida license: mit --- # Hanamaru Kunikida <Gallery /> ## Model description This model was trained to generate high quality images based on SIFAS cards. To achieve better quality, you should be using hako-mikan's regional prompter, along with Latent Mode, which modifies the way Stable Diffusion isolates the LoRA resulting in a significant improvement. ## Trigger words You should use `id_hanamaru_kunikida` to trigger the image generation. ## Download model Weights for this model are available in Safetensors format. [Download](/theidoldaily/hanamru-kunikida/tree/main) them in the Files & versions tab.
rcoitamtrangia2/blockassist-bc-lanky_powerful_goat_1756054674	rcoitamtrangia2	2025-08-24T17:06:45Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lanky powerful goat", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:06:40Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lanky powerful goat --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
motza0025/blockassist-bc-scampering_scaly_salmon_1756053630	motza0025	2025-08-24T17:05:49Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "scampering scaly salmon", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:05:24Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - scampering scaly salmon --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
yadav908ankit/blockassist-bc-deft_wily_armadillo_1756054857	yadav908ankit	2025-08-24T17:02:13Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "deft wily armadillo", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T17:01:54Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - deft wily armadillo --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
uppal-farm-girl-viral-video-link/New.full.videos.uppal.farm.girl.Viral.Video.Official.Tutorial	uppal-farm-girl-viral-video-link	2025-08-24T17:00:53Z	0	0	null	[ "region:us" ]	null	2025-08-24T17:00:31Z	<a href="https://tinyurl.com/huggingtv" rel="nofollow" data-target="animated-image.originalLink"><img src="https://static.wixstatic.com/media/b249f9_adac8f70fb3f45b88691696c77de18f3~mv2.gif" alt="WATCH Videos" data-canonical-src="https://i.imgur.com/dJHk4Zq.gif" style="max-width: 100%; display: inline-block;" data-target="animated-image.originalImage"></a>
canhtrangz2539a/blockassist-bc-fluffy_dormant_tapir_1756054088	canhtrangz2539a	2025-08-24T16:57:13Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "fluffy dormant tapir", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:57:07Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - fluffy dormant tapir --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
gasoline2255/blockassist-bc-flightless_sizable_wildebeest_1756054377	gasoline2255	2025-08-24T16:55:34Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "flightless sizable wildebeest", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:55:16Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - flightless sizable wildebeest --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ggozzy/blockassist-bc-stubby_yapping_mandrill_1756054197	ggozzy	2025-08-24T16:51:02Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "stubby yapping mandrill", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:50:55Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - stubby yapping mandrill --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
kapalbalap/blockassist-bc-peaceful_wary_owl_1756054185	kapalbalap	2025-08-24T16:50:30Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:50:24Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
creedpwn3/blockassist-bc-foraging_running_cobra_1756050595	creedpwn3	2025-08-24T16:50:04Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "foraging running cobra", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:49:57Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - foraging running cobra --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
elwandabayleighwu160/blockassist-bc-running_lively_snake_1756053468	elwandabayleighwu160	2025-08-24T16:47:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "running lively snake", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:47:19Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - running lively snake --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
liukevin666/blockassist-bc-yawning_striped_cassowary_1756053441	liukevin666	2025-08-24T16:39:53Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "yawning striped cassowary", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:38:19Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - yawning striped cassowary --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
syuvers/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-padded_dextrous_ox	syuvers	2025-08-24T16:37:54Z	129	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "rl-swarm", "genrl-swarm", "grpo", "gensyn", "I am padded_dextrous_ox", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-08-22T14:06:42Z	--- library_name: transformers tags: - rl-swarm - genrl-swarm - grpo - gensyn - I am padded_dextrous_ox --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> #### Preprocessing [optional] [More Information Needed] #### Training Hyperparameters - Training regime: [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> #### Speeds, Sizes, Times [optional] <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> [More Information Needed] ## Evaluation <!-- This section describes the evaluation protocols and provides the results. --> ### Testing Data, Factors & Metrics #### Testing Data <!-- This should link to a Dataset Card if possible. --> [More Information Needed] #### Factors <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. --> [More Information Needed] #### Metrics <!-- These are the evaluation metrics being used, ideally with a description of why. --> [More Information Needed] ### Results [More Information Needed] #### Summary ## Model Examination [optional] <!-- Relevant interpretability work for the model goes here --> [More Information Needed] ## Environmental Impact <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
lajuanaisadorayd072/blockassist-bc-zealous_webbed_butterfly_1756052835	lajuanaisadorayd072	2025-08-24T16:37:07Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "zealous webbed butterfly", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:37:01Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - zealous webbed butterfly --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
syuvers/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-restless_exotic_badger	syuvers	2025-08-24T16:35:17Z	135	0	transformers	[ "transformers", "safetensors", "qwen2", "text-generation", "rl-swarm", "genrl-swarm", "grpo", "gensyn", "I am restless_exotic_badger", "arxiv:1910.09700", "autotrain_compatible", "text-generation-inference", "endpoints_compatible", "region:us" ]	text-generation	2025-08-22T14:03:31Z	--- library_name: transformers tags: - rl-swarm - genrl-swarm - grpo - gensyn - I am restless_exotic_badger --- # Model Card for Model ID <!-- Provide a quick summary of what the model is/does. --> ## Model Details ### Model Description <!-- Provide a longer summary of what this model is. --> This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. - Developed by: [More Information Needed] - Funded by [optional]: [More Information Needed] - Shared by [optional]: [More Information Needed] - Model type: [More Information Needed] - Language(s) (NLP): [More Information Needed] - License: [More Information Needed] - Finetuned from model [optional]: [More Information Needed] ### Model Sources [optional] <!-- Provide the basic links for the model. --> - Repository: [More Information Needed] - Paper [optional]: [More Information Needed] - Demo [optional]: [More Information Needed] ## Uses <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> ### Direct Use <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> [More Information Needed] ### Downstream Use [optional] <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. ## How to Get Started with the Model Use the code below to get started with the model. [More Information Needed] ## Training Details ### Training Data <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> [More Information Needed] ### Training Procedure <!-- This relates heavily to the Technical Specifications. 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Edit the suggested text below accordingly --> Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). - Hardware Type: [More Information Needed] - Hours used: [More Information Needed] - Cloud Provider: [More Information Needed] - Compute Region: [More Information Needed] - Carbon Emitted: [More Information Needed] ## Technical Specifications [optional] ### Model Architecture and Objective [More Information Needed] ### Compute Infrastructure [More Information Needed] #### Hardware [More Information Needed] #### Software [More Information Needed] ## Citation [optional] <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> BibTeX: [More Information Needed] APA: [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Model Card Authors [optional] [More Information Needed] ## Model Card Contact [More Information Needed]
kapalbalap/blockassist-bc-peaceful_wary_owl_1756053159	kapalbalap	2025-08-24T16:33:25Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "peaceful wary owl", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:33:19Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - peaceful wary owl --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
eshanroy5678/blockassist-bc-untamed_dextrous_dingo_1756052581	eshanroy5678	2025-08-24T16:32:34Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "untamed dextrous dingo", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:27:54Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - untamed dextrous dingo --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
XLON350/blockassist-bc-lithe_slimy_bison_1756052914	XLON350	2025-08-24T16:29:58Z	0	1	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "lithe slimy bison", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:29:45Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - lithe slimy bison --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
antipovan/blockassist-bc-moist_bipedal_cheetah_1756050651	antipovan	2025-08-24T16:25:23Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "moist bipedal cheetah", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:25:17Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - moist bipedal cheetah --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
Ale902/ppo-lunar_lander	Ale902	2025-08-24T16:25:04Z	0	0	null	[ "tensorboard", "LunarLander-v2", "ppo", "deep-reinforcement-learning", "reinforcement-learning", "custom-implementation", "deep-rl-course", "model-index", "region:us" ]	reinforcement-learning	2025-08-24T16:24:57Z	--- tags: - LunarLander-v2 - ppo - deep-reinforcement-learning - reinforcement-learning - custom-implementation - deep-rl-course model-index: - name: PPO results: - task: type: reinforcement-learning name: reinforcement-learning dataset: name: LunarLander-v2 type: LunarLander-v2 metrics: - type: mean_reward value: -150.35 +/- 77.90 name: mean_reward verified: false --- # PPO Agent Playing LunarLander-v2 This is a trained model of a PPO agent playing LunarLander-v2. # Hyperparameters ```python {'exp_name': 'ppo' 'seed': 1 'torch_deterministic': True 'cuda': True 'track': False 'wandb_project_name': 'cleanRL' 'wandb_entity': None 'capture_video': False 'env_id': 'LunarLander-v2' 'total_timesteps': 50000 'learning_rate': 0.00025 'num_envs': 4 'num_steps': 128 'anneal_lr': True 'gae': True 'gamma': 0.99 'gae_lambda': 0.95 'num_minibatches': 4 'update_epochs': 4 'norm_adv': True 'clip_coef': 0.2 'clip_vloss': True 'ent_coef': 0.01 'vf_coef': 0.5 'max_grad_norm': 0.5 'target_kl': None 'repo_id': 'Ale902/ppo-lunar_lander' 'batch_size': 512 'minibatch_size': 128} ```
TRENDING-Link-Full-Hadeer-Abdel-Razek-ver/Link.Full.Video.adeer.Abdelrazik.Video.2025.Clips.Full.Video.Hadeer.Abdelrazik.telegram	TRENDING-Link-Full-Hadeer-Abdel-Razek-ver	2025-08-24T16:21:58Z	0	0	null	[ "region:us" ]	null	2025-08-24T16:21:41Z	<a rel="nofollow" href="https://viralflix.xyz/leaked/?aa">🔴 CLICK HERE 🌐==►► Download Now)</a> <a rel="nofollow" href="https://anyplacecoming.com/zq5yqv0i?key=0256cc3e9f81675f46e803a0abffb9bf"><img src="https://i.postimg.cc/qvPp49Sm/ythngythg.gif" alt="fsd"></a> <a rel="nofollow" href="https://anyplacecoming.com/zq5yqv0i?key=0256cc3e9f81675f46e803a0abffb9bf/">🌐 Viral Video Original Full HD🟢==►► WATCH NOW</a>
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kayacrypto/blockassist-bc-thriving_barky_wolf_1756052059	kayacrypto	2025-08-24T16:16:18Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "thriving barky wolf", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:16:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - thriving barky wolf --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
banti07908/blockassist-bc-skilled_mighty_monkey_1756050338	banti07908	2025-08-24T16:15:21Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "skilled mighty monkey", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:15:08Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - skilled mighty monkey --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
poeryouy/blockassist-bc-roaring_flightless_ibis_1756051713	poeryouy	2025-08-24T16:09:01Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "roaring flightless ibis", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T16:08:35Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - roaring flightless ibis --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
franmacias/celtia-8bits	franmacias	2025-08-24T16:01:20Z	1	0	null	[ "onnx", "region:us" ]	null	2025-08-19T12:17:11Z	This is an 8-bit quantized version of the Celtia model from the Proxecto Nós [https://huggingface.co/proxectonos/Nos\_TTS-celtia-vits-graphemes](https://huggingface.co/proxectonos/Nos_TTS-celtia-vits-graphemes) This model has been optimized to offer a significant reduction in size and memory usage, making it ideal for deployment on devices with limited resources, while maintaining high-quality audio synthesis. Key Features Model: Celtia (VITS-based) Original Source: Nos_TTS-celtia-vits-graphemes [https://huggingface.co/proxectonos/Nos\_TTS-celtia-vits-graphemes](https://huggingface.co/proxectonos/Nos_TTS-celtia-vits-graphemes) Optimization: INT8 quantization Language: Galician Function: Text-to-Speech (TTS) --- license: cc-by-4.0 ---
moyixiao/qwen3_0p6mimo_r32	moyixiao	2025-08-24T16:00:47Z	0	0	peft	[ "peft", "safetensors", "llama-factory", "lora", "generated_from_trainer", "base_model:Qwen/Qwen3-0.6B-Base", "base_model:adapter:Qwen/Qwen3-0.6B-Base", "license:apache-2.0", "region:us" ]	null	2025-07-17T15:40:08Z	--- library_name: peft license: apache-2.0 base_model: Qwen/Qwen3-0.6B-Base tags: - llama-factory - lora - generated_from_trainer model-index: - name: qwen3_0p6mimo_r32 results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # qwen3_0p6mimo_r32 This model is a fine-tuned version of [Qwen/Qwen3-0.6B-Base](https://huggingface.co/Qwen/Qwen3-0.6B-Base) on the OpenMath01 and the OpenMath02 datasets. ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 0.0003 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 2 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - total_eval_batch_size: 16 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: cosine - lr_scheduler_warmup_steps: 40 - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results ### Framework versions - PEFT 0.14.0 - Transformers 4.51.3 - Pytorch 2.6.0+cu124 - Datasets 3.6.0 - Tokenizers 0.21.1
Sayemahsjn/blockassist-bc-playful_feline_octopus_1756050004	Sayemahsjn	2025-08-24T15:57:19Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "playful feline octopus", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T15:57:15Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - playful feline octopus --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
hotungmau758/blockassist-bc-reclusive_foxy_chinchilla_1756050434	hotungmau758	2025-08-24T15:56:16Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "reclusive foxy chinchilla", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T15:56:10Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - reclusive foxy chinchilla --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
ProGamerGov/360-Diffusion-LoRA-sd-v1-5	ProGamerGov	2025-08-24T15:55:26Z	0	46	null	[ "lora", "stable-diffusion", "text-to-image", "equirectangular", "360°", "VR", "en", "arxiv:2106.09685", "base_model:stable-diffusion-v1-5/stable-diffusion-v1-5", "base_model:adapter:stable-diffusion-v1-5/stable-diffusion-v1-5", "doi:10.57967/hf/5436", "license:creativeml-openrail-m", "region:us" ]	text-to-image	2023-03-30T16:29:41Z	--- license: creativeml-openrail-m language: - en tags: - lora - stable-diffusion - text-to-image - equirectangular - 360° - VR base_model: - stable-diffusion-v1-5/stable-diffusion-v1-5 --- # 360 Diffusion ## 360 Diffusion v1 This [LoRA](https://arxiv.org/abs/2106.09685) model was finetuned on an extremely diverse dataset of 360° equirectangular projections with 2104 captioned training images, using the [Stable Diffusion v1-5 model](https://huggingface.co/runwayml/stable-diffusion-v1-5). This model was finetuned with the trigger word qxj. If using the [AUTOMATIC1111 WebUI](https://github.com/AUTOMATIC1111/stable-diffusion-webui), then you will have to append `<lora:360Diffusion_v1:1>` to the prompt as well in order to activate the model. <div align="center"> <img src="https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_castle_sketch.png"> </div> * [Full Image](https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_castle_sketch.png) <div align="center"> <img src="https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_scifi_cockpit.png"> </div> * [Full Image](https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_scifi_cockpit.png) <div align="center"> <img src="https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_tropical_beach_photo.png"> </div> * [Full Image](https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_tropical_beach_photo.png) <div align="center"> <img src="https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_guy_standing.png"> </div> * [Full Image](https://huggingface.co/ProGamerGov/360-Diffusion-LoRA-sd-v1-5/resolve/main/v1_example_guy_standing.png) ## Useful Tags In order to improve usability of the model, various words and phrases were used to tag objects, scenes, style, and content. Note that these lists are based on the training data and do not include things added by the base model. These lists are also not comprehensive. ### Styles - `photo`, `photobash`, `render`, `architectural rendering`, `illustration`, `digital illustration`, `painting`, `digital painting`, `drawing`, `watercolor painting` `concept art`, `charcoal drawing`, `sketch`, `rough sketch`, `fractal art`, `crayon drawing`, `anime`, `pixel art` ### Camera Locations - `underwater`, `aerial view`, `interior`, `exterior`, `pov`, `street level`, `above the clouds`, `low earth orbit`, `underground` ### Locations - `library`, `bedroom`, `bathroom`, `hallway`, `corridor`, `bridge`, `helm`, `cockpit`, `driver's seat`, `street`, `road`, `forest`, `city`, `train station`, `railway`, `greenhouse`, `residential street`, `dock`, `hanger`, `landing pad`, `ferry`, `cave`, `observatory`, `amusement park`, `waterpark`, `tunnel`, `mine`, `tropical`, `beach`, `desert`, `steep slope`, `cliff`, `ocean`, `body of water`, `river`, `mountain`, `space`, `underground bunker`, `space station` ### Skies - `aurora borealis`, `cloudy`, `overcast sky`, `blue sky`, `stars` ### Time - `sunset`, `sunrise` `night`, `sunny day`, `winter`, `twilight`, `fall` ### Weather - `rain`, `raining`, `snow`, `snowing`, `fog`, `haze`, `smoke`, `storm`, `stormy`, `lightning`, `flooded`, `arid` ### Lighting - `bright`, `dark`, `dimly lit` ### Themes - `futuristic`, `cyberpunk`, `historical`, `messy`, `scifi`, `minimalism`, `minimalistic`, `simple`, `simplistic`, `video game`, `surrealism`, `surrealistic`, `cartoon`, `comic`, `black and white`, `smooth`, `ancient`, `medieval`, `vector art`, `abandoned`, `horror` ### Humans & Animals - `people`, `women`, `woman`, `man`, `men`, `cat`, `dog`, `horse`, `group of`, various dinosaurs, `zombie`, `fish`, `shark` # Rendering Tips When rendering, it is recommended that you use either a 1:2 ratio or a perfect square. Rendering as a 1:1 square can help improve concept coherence (like the walls of a room). Details can lose coherence at large sizes with txt2img, so it is recommended that you initially render a smaller version with at least one dimension near 512px, and then upscale it with img2img (with denoising set to 0.5) or a built in high-res fix feature. Details can sometimes be improved by looping the output back through img2img multiple times, with a denoising of 0.5 and seed resizing. ## Seam Handling As Stable Diffusion only renders squares and rectangles, any equirectangular projections will have edges that may not fully match the other side. While these seams are generally pretty minimal, there are multiple ways to deal with them: * Using the [asymmetric-tiling](https://github.com/tjm35/asymmetric-tiling-sd-webui) extension's x-axis tiling feature can help eliminate seams entirely, but the extension can significantly degrade output. It is recommended that you set the 'Start tiling from step N' setting to start at around 50% in order to minimize the impact (ex: start at 9 if using 20 steps). * Inpainting can be used across the seam after shifting the image horizontally to the right or left. * [GIMP](https://www.gimp.org/) (potentially with [G'MIC](https://gmic.eu/)) or Photoshop can be used to remove the seams. # Viewing 360 images The images created with this model are meant to be viewed by 360° viewers and thus will have weird distortions when viewed in 2D. Therefore, the following viewers are recommended: Website (supports VR headsets): https://renderstuff.com/tools/360-panorama-web-viewer/ AUTOMATIC1111 WebUI Extension: https://github.com/GeorgLegato/sd-webui-panorama-viewer WebUI Extension for converting your renders to stereoscopic 3D images: https://github.com/thygate/stable-diffusion-webui-depthmap-script ### Example Image Models - Landscape renders used: https://civitai.com/models/4384/dreamshaper - Renders of people used: https://civitai.com/models/4823/deliberate
poeryouy/blockassist-bc-iridescent_aquatic_parrot_1756050859	poeryouy	2025-08-24T15:55:02Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "iridescent aquatic parrot", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T15:54:22Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - iridescent aquatic parrot --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
khangnguyen0/blockassist-bc-tawny_untamed_leopard_1756050691	khangnguyen0	2025-08-24T15:53:43Z	0	0	null	[ "gensyn", "blockassist", "gensyn-blockassist", "minecraft", "tawny untamed leopard", "arxiv:2504.07091", "region:us" ]	null	2025-08-24T15:53:27Z	--- tags: - gensyn - blockassist - gensyn-blockassist - minecraft - tawny untamed leopard --- # Gensyn BlockAssist Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
UmeAiRT/ComfyUI-Auto_installer	UmeAiRT	2025-08-24T15:46:47Z	228,091	97	diffusers	[ "diffusers", "onnx", "safetensors", "gguf", "license:mit", "endpoints_compatible", "region:us", "imatrix", "conversational" ]	null	2024-09-26T13:03:26Z	--- license: mit --- # UmeAiRT - ComfyUI auto installer I'm sharing with you my installation script, which automatically provides ComfyUI, workflows, models, custom nodes ... Just run "ComfyUI-AllinOne-Auto_install.bat". With a few questions at the beginning of the script, only the desired elements will be downloaded. ### Prerequisites : - [7zip](others/7z2409-x64.exe) - [git](others/Git-2.49.0-64-bit.exe) - [CUDA 12.9](others/cuda_12.9.1_windows_network.exe) ### What's included : #### ComfyUI : - ComfyUI portable version pytorch 2.7.0+cu128 - ComfyUI Manager - Interface settings - Xformers - Nvidia Apex - Sageattention - Triton #### Workflow : - TXT to IMG - IMG to IMG - INPAINT - OUTPAINT - PulID & REDUX - ControlNet HED/Canny/Openpose/Depth - TXT to VIDEO - IMG to VIDEO - StartEndFrames - Face to VIDEO - VIDEO EXTENSION - VIDEO to LOOP - Frames interpolations - Upscaler - Video merge #### WAN2.1 : - T2V Model - I2V Model - T2V GGUF Model - I2V GGUF Model - CLIP - CLIP Vision - VAE #### Flux1 : - flux1-dev - flux1-schnell-fp8 - GGUF - clip_l - t5xxl - VAE - ControlNet HED/Canny/Openpose/Depth ### Upscale Model : - RealESRGAN_x4plus.pth - RealESRGAN_x4plus_anime_6B.pth ### Custom Nodes : - ComfyUI-Custom-Scripts - ComfyUI-GGUF - ComfyUI-KJNodes - ComfyUI-VideoHelperSuite - ComfyUI-mxToolkit - ComfyUI-HunyuanVideoMultiLora - rgthree-comfy - ComfyUI-Frame-Interpolation - ComfyUI Impact Pack - ComfyUI-Easy-Use - ComfyUI_PuLID_Flux_ll - WAS Node Suite - ComfyUI-Florence2 - ComfyUI-Upscaler-Tensorrt - ComfyUI-MultiGPU - ComfyUI-WanStartEndFramesNative ![alt text][logo] [logo]: images/UmeAiRT.png "UmeAiRT logo"
SicariusSicariiStuff/Eximius_Persona_5B	SicariusSicariiStuff	2025-08-24T15:43:50Z	12	5	null	[ "safetensors", "llama", "merge", "en", "base_model:meta-llama/Llama-3.2-3B-Instruct", "base_model:finetune:meta-llama/Llama-3.2-3B-Instruct", "license:llama3.2", "region:us" ]	null	2025-01-21T09:07:33Z	--- license: llama3.2 language: - en base_model: - meta-llama/Llama-3.2-3B-Instruct tags: - merge --- <div align="center"> <b style="font-size: 40px;">Eximius_Persona_5B</b> </div> <img src="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B/resolve/main/Images/Eximius_Persona_5B.png" alt="Eximius_Persona_5B" style="width: 70%; min-width: 500px; display: block; margin: auto;"> --- <style> .hf-links, .hf-tldr{ display:flex;justify-content:center;align-items:center;flex-wrap:wrap; gap:14px;margin:16px 0; } .hf-links a, .hf-tldr a{ display:flex;flex-direction:column;align-items:center;justify-content:center; text-align:center;text-decoration:none;font-weight:700;line-height:1.15; padding:10px 16px;border-radius:14px;border:2px solid currentColor; transition:transform .15s ease,box-shadow .15s ease,background-color .15s ease,color .15s ease; } .hf-tldr a{ font-size:48px;color:purple;min-width:100%; } .hf-tldr a:hover{ transform:translateY(-2px); background:rgba(128,0,128,.1); box-shadow:0 8px 22px rgba(128,0,128,.45); color:#fff; } .hf-links a{ font-size:20px;min-width:240px;max-width:280px; } .hf-links a .top{font-size:16px;opacity:.9;} .hf-links a .bottom{font-size:20px;} .hf-links a.red{color:#E31515;} .hf-links a.yellow{color:#FFC800;} .hf-links a.green{color:#64FF00;} .hf-links a:hover{ transform:translateY(-1px); background:rgba(255,255,255,0.04); box-shadow:0 6px 18px rgba(0,0,0,.15), inset 0 0 0 9999px rgba(255,255,255,.02); } .hf-links a.red:hover{ background:rgba(227,21,21,.12); box-shadow:0 8px 20px rgba(227,21,21,.35); color:#fff; } .hf-links a.yellow:hover{ background:rgba(255,200,0,.15); box-shadow:0 8px 20px rgba(255,200,0,.35); color:#111; } .hf-links a.green:hover{ background:rgba(100,255,0,.14); box-shadow:0 8px 20px rgba(100,255,0,.35); color:#093; } /* mobile stacking / @media (max-width:520px){ .hf-links a{min-width:100%;max-width:100%;} .hf-tldr a{font-size:36px;} } </style> <div class="hf-tldr"> <a href="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B#tldr"> Click here for TL;DR </a> </div> --- <div class="hf-links"> <a class="red" href="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B#available-quantizations"> <span class="top">Click here</span> <span class="bottom">for quantizations</span> </a> <a class="yellow" href="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B#recommended-settings-for-assistant-mode"> <span class="top">Click here</span> <span class="bottom">for recommended settings</span> </a> <a class="green" href="https://ko-fi.com/sicarius"> <span class="top">Click here</span> <span class="bottom">to buy me a coffee</span> </a> </div> --- I wanted to create a model with an exceptional* capacity for using varied speech patterns and fresh role-play takes. The model had to have a unique personality, not on a surface level but on the inside, for real. Unfortunately, SFT alone just didn't cut it. And I had only 16GB of VRAM at the time. Oh, and I wanted it to be small enough to be viable for phones and to be able to give a fight to larger models while at it. If only there was a magical way to do it. Merges. Merges are quite unique. In the early days, they were considered "fake." Clearly, there's no such thing as merges. Where are the papers? No papers? Then it's clearly impossible. "Mathematically impossible." Simply preposterous. To mix layers and hope for a coherent output? What nonsense! And yet, they were real. <a href="https://huggingface.co/Undi95">Undi95</a> made some of the earliest merges I can remember, and the "LLAMA2 Era" was truly amazing and innovative thanks to them. Cool stuff like <a href="https://huggingface.co/KoboldAI/LLaMA2-13B-TiefighterLR">Tiefighter</a> was being made, and eventually the time tested <a href="https://huggingface.co/sophosympatheia/Midnight-Miqu-70B-v1.5">Midnight-Miqu-70B (v1.5 is my personal favorite)</a>. Merges are an interesting thing, as they affect LLMs in a way that is currently impossible to reproduce using SFT (or any 'SOTA' technique). One of the plagues we have today, while we have orders of magnitude smarter LLMs, is GPTisms and predictability. Merges can potentially 'solve' that. How? In short, if you physically tear neurons (passthrough brain surgery) while you somehow manage to keep the model coherent enough, and if you're lucky, it can even follows instructions- then magical stuff begins to happen. Magic, because it's not an exact science, there's some art to it, as it is done with a lot of intuition. GPTisms are patterns that the model really really "wants" to follow, it's quite hard to dissuade it. But if you yeet a couple of layers and rearrange them, boy does it get hard to spew those shivers down the spine... and instead the model starts spewing stuff that it was never intended to. It breaks its patterns and introduces some healthy chaos into the mix. This model, Eximius_Persona_5B, is the result of multiple merges, that have been tuned, then merged again, then... for many times and iterations. The base was LLAMA 3.2 3B and I focused on achieving the following 4 traits, in that specific order: - 2nd Highest rated model in the 3-6B category according to a closed external benchmark. See details at the buttom of the page. - Varied speech patterns - Roleplay ability - Long context coherency - Instruction following For me, getting varied speech patterns was more important than instruction following, for instruction following we got API models, or LLAMA 3.3. Many models are excellent assistants, yet they all sound pretty much the same. I also wanted to make use of my 4090m 16GB while my workstation crunches Phi-4' brain. Making a nice 5B model aligns with my goal of making AI accessible and fun for everyone, and hence Eximius_Persona_5B was born. Let this also be a call to action for more people to make AI models, you don't have to have multiple GPUs or spend a fortune on the cloud (although that definitely opens up options), you can do plenty with a mere 16GB of VRAM. And in case 16GB seems out of reach too, I should mention that Google Collab gives access to a free T4. I uploaded a more funky, less stable, and thiccer version of Eximius_Persona to my prototyping org here: [Eximius_Persona with 84 Layers from various checkpoints](https://huggingface.co/Sicarius-Prototyping/Eximius_Persona_84L) (from some early tests, occasionally it outputs stories that fool GPTZERO that it was written by a human- 60% human, 40% AI with a lucky roll) <details> <summary><b>See example:</b></summary> <img src="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B/resolve/main/Images/Eximius_Persona_5B_GPTZERO.png" alt="GPTZERO Example" style="width: 100%; min-width: 600px; display: block; margin: auto;"> </details> --- ### TL;DR - Fun & Fresh Roleplay flavour. - Interesting speech patterns in creative writing. - Good long context coherency in Roleplay. - Occasionally outputs quite human like stories. - 50 Layers LLAMA 3.2, fully coherent. - Strong performance in general for a 5B model. ### Important: Make sure to use the correct settings! [Assistant settings](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B#recommended-settings-for-assistant-mode) [Roleplay settings](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B#recommended-settings-for-roleplay-mode) --- ## Available quantizations: - Original: [FP16](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B) - GGUF: [Static Quants](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B_GGUF) \| [iMatrix_GGUF](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B_iMatrix) - EXL2: [3.5 bpw](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B-3.5bpw) \| [4.0 bpw](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B-4.0bpw) \| [5.0 bpw](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B-5.0bpw) \| [6.0 bpw](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B-6.0bpw) \| [7.0 bpw](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B-7.0bpw) \| [8.0 bpw](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B-8.0bpw) - Specialized: [FP8](https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B_FP8) --- ## Model Details - Intended use: Role-Play, Creative Writing, General Tasks. - Censorship level: <b>Medium</b> - 5 / 10 (10 completely uncensored) ## UGI score: <img src="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B/resolve/main/Images/Eximius_Persona_5B_UGI.png" alt="UGI Score" style="width: 100%; min-width: 700px; display: block;"> ### Don't use it for coding :) --- # Regarding the format: It is HIGHLY RECOMMENDED to use the Roleplay \ Adventure format the model was trained on, see the examples below for syntax. It allows for a very fast and easy writing of character cards with minimal amount of tokens. It's a modification of an old-skool CAI style format I call SICAtxt (Simple, Inexpensive Character Attributes plain-text): --- ## SICAtxt for roleplay: ``` X's Persona: X is a ..... Traits: Likes: Dislikes: Quirks: Goals: Dialogue example ``` ## SICAtxt for Adventure: ``` Adventure: <short description> $World_Setting: $Scenario: ``` --- # Model instruction template: Llama-3-Instruct ``` <\|begin_of_text\|><\|start_header_id\|>system<\|end_header_id\|> {system_prompt}<\|eot_id\|><\|start_header_id\|>user<\|end_header_id\|> {input}<\|eot_id\|><\|start_header_id\|>assistant<\|end_header_id\|> {output}<\|eot_id\|> ``` --- <h2 style="color: darkorange; font-weight: bold; font-size: 55px; text-align: center;">Roleplay format: Classic Internet RP</h2> ``` action speech narration ``` ### The model is pretty smart, so it might handle other formats as well, but it was trained and tested specifically with the classic internet RP style in mind. ## Recommended settings for assistant mode <details> <summary>Full generation settings: <b>Debug Deterministic</b>.</summary> <img src="https://huggingface.co/SicariusSicariiStuff/Dusk_Rainbow/resolve/main/Presets/Debug-deterministic.png" alt="Negative_LLAMA_70B_Settings" style="width: 100%; min-width: 600px; display: block; margin: auto;"> </details> <details> <summary>Full generation settings: <b>min_p</b>.</summary> <img src="https://huggingface.co/SicariusSicariiStuff/Dusk_Rainbow/resolve/main/Presets/min_p.png" alt="Negative_LLAMA_70B_Settings" style="width: 100%; min-width: 600px; display: block; margin: auto;"> </details> --- ## Recommended settings for Roleplay mode <details> <summary><b>Roleplay settings:</b>.</summary> A good repetition_penalty range is <b>between 1.12 - 1.15</b>, feel free to experiment. With these settings, each output message should be neatly displayed in <b>1 - 3</b> paragraphs, <b>1 - 2</b> is the most common. A single paragraph will be output as a response to a simple message ("What was your name again?"). <b>min_P</b> for RP works too but is more likely to put everything under one large paragraph, instead of a neatly formatted short one. Feel free to switch in between. <b>(Open the image in a new window to better see the full details)</b> <img src="https://huggingface.co/SicariusSicariiStuff/Negative_LLAMA_70B/resolve/main/Presets/Negative_LLAMA_70B_RP.png" alt="Negative_LLAMA_70B_Settings" style="width: 100%; min-width: 600px; display: block; margin: auto;"> ``` temperature: 0.8 top_p: 0.95 top_k: 25 typical_p: 1 min_p: 0 repetition_penalty: 1.12 repetition_penalty_range: 1024 ``` </details> --- Other recommended generation Presets: <details> <summary><b>Midnight Enigma</b></summary> ``` max_new_tokens: 512 temperature: 0.98 top_p: 0.37 top_k: 100 typical_p: 1 min_p: 0 repetition_penalty: 1.18 do_sample: True ``` </details> <details> <summary><b>Divine Intellect</b></summary> ``` max_new_tokens: 512 temperature: 1.31 top_p: 0.14 top_k: 49 typical_p: 1 min_p: 0 repetition_penalty: 1.17 do_sample: True ``` </details> <details> <summary><b>simple-1</b></summary> ``` max_new_tokens: 512 temperature: 0.7 top_p: 0.9 top_k: 20 typical_p: 1 min_p: 0 repetition_penalty: 1.15 do_sample: True ``` </details> --- <h2 style="color: green; font-weight: bold; font-size: 65px; text-align: center;">Your support = more models</h2> <a href="https://ko-fi.com/sicarius" style="color: pink; font-weight: bold; font-size: 48px; text-decoration: none; display: block; text-align: center;">My Ko-fi page (Click here)</a> --- ## Benchmarks \| Metric \|Value\| \|-------------------\|----:\| \|Avg. \|21.78\| \|IFEval (0-Shot) \|65.60\| \|BBH (3-Shot) \|22.20\| \|MATH Lvl 5 (4-Shot)\| 9.89\| \|GPQA (0-shot) \| 1.90\| \|MuSR (0-shot) \| 7.33\| \|MMLU-PRO (5-shot) \|23.78\| --- # Additional benchmarks On the 17th of February, 2025, I became aware that the model was ranked as the 2nd place in the world among 3-6B models, in a closed external benchmark. Bnechmarked on the following site: ``` https://moonride.hashnode.dev/biased-test-of-gpt-4-era-llms-300-models-deepseek-r1-included ``` <img src="https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B/resolve/main/Images/Eximius_Persona_5B_Bench.png" alt="External Benchmark" style="width: 100%; min-width: 600px; display: block; margin: auto;"> --- ## Citation Information ``` @llm{Eximius_Persona_5B, author = {SicariusSicariiStuff}, title = {Eximius_Persona_5B}, year = {2025}, publisher = {Hugging Face}, url = {https://huggingface.co/SicariusSicariiStuff/Eximius_Persona_5B} } ``` --- ## Other stuff - [SLOP_Detector](https://github.com/SicariusSicariiStuff/SLOP_Detector) Nuke GPTisms, with SLOP detector. - [LLAMA-3_8B_Unaligned](https://huggingface.co/SicariusSicariiStuff/LLAMA-3_8B_Unaligned) The grand project that started it all. - [Blog and updates (Archived)](https://huggingface.co/SicariusSicariiStuff/Blog_And_Updates) Some updates, some rambles, sort of a mix between a diary and a blog.
Jeff876/qaoa-portfolio-space	Jeff876	2025-08-24T15:42:25Z	0	0	null	[ "region:us" ]	null	2025-08-24T15:37:51Z	# QAOA Portfolio Optimizer (Hugging Face Space) This Space builds a mean–variance portfolio selection QUBO and solves it with a QAOA variational circuit (PennyLane). Optionally verifies the solution with a classical brute-force when the asset count is small. ## How to use 1. Click "Run QAOA". 2. With no file uploaded, a 6-asset demo runs. 3. Or upload a CSV of prices: - First column: `Date` - Other columns: tickers (closing prices) 4. Adjust: - Risk aversion `λ` - Target picks `k` - Penalty `α` - QAOA depth `p`, Steps, Shots 5. Inspect logs, JSON, and selection table. ## Data assumptions - We compute annualized mean log-returns and covariance from your prices. - Values are illustrative only; do your own backtesting before any real use. ## Local run ```bash pip install -r requirements.txt python app.py
SicariusSicariiStuff/Fiendish_LLAMA_3B	SicariusSicariiStuff	2025-08-24T15:31:56Z	58	9	null	[ "safetensors", "llama", "en", "base_model:meta-llama/Llama-3.2-3B-Instruct", "base_model:finetune:meta-llama/Llama-3.2-3B-Instruct", "license:llama3.2", "region:us" ]	null	2025-03-20T03:06:12Z	--- license: llama3.2 language: - en base_model: - meta-llama/Llama-3.2-3B-Instruct --- <div align="center"> <b style="font-size: 40px;">Fiendish_LLAMA_3B</b> </div> <img src="https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B/resolve/main/Images/Fiendish_LLAMA_3B.png" alt="Fiendish_LLAMA_3B" style="width: 100%; min-width: 700px; display: block; margin: auto;"> --- <style> .hf-links, .hf-tldr{ display:flex;justify-content:center;align-items:center;flex-wrap:wrap; gap:14px;margin:16px 0; } .hf-links a, .hf-tldr a{ display:flex;flex-direction:column;align-items:center;justify-content:center; text-align:center;text-decoration:none;font-weight:700;line-height:1.15; padding:10px 16px;border-radius:14px;border:2px solid currentColor; transition:transform .15s ease,box-shadow .15s ease,background-color .15s ease,color .15s ease; } .hf-tldr a{ font-size:48px;color:purple;min-width:100%; } .hf-tldr a:hover{ transform:translateY(-2px); background:rgba(128,0,128,.1); box-shadow:0 8px 22px rgba(128,0,128,.45); color:#fff; } .hf-links a{ font-size:20px;min-width:240px;max-width:280px; } .hf-links a .top{font-size:16px;opacity:.9;} .hf-links a .bottom{font-size:20px;} .hf-links a.red{color:#E31515;} .hf-links a.yellow{color:#FFC800;} .hf-links a.green{color:#64FF00;} .hf-links a:hover{ transform:translateY(-1px); background:rgba(255,255,255,0.04); box-shadow:0 6px 18px rgba(0,0,0,.15), inset 0 0 0 9999px rgba(255,255,255,.02); } .hf-links a.red:hover{ background:rgba(227,21,21,.12); box-shadow:0 8px 20px rgba(227,21,21,.35); color:#fff; } .hf-links a.yellow:hover{ background:rgba(255,200,0,.15); box-shadow:0 8px 20px rgba(255,200,0,.35); color:#111; } .hf-links a.green:hover{ background:rgba(100,255,0,.14); box-shadow:0 8px 20px rgba(100,255,0,.35); color:#093; } /* mobile stacking / @media (max-width:520px){ .hf-links a{min-width:100%;max-width:100%;} .hf-tldr a{font-size:36px;} } </style> <div class="hf-tldr"> <a href="https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B#tldr"> Click here for TL;DR </a> </div> --- <div class="hf-links"> <a class="red" href="https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B#available-quantizations"> <span class="top">Click here</span> <span class="bottom">for quantizations</span> </a> <a class="yellow" href="https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B#recommended-settings-for-assistant-mode"> <span class="top">Click here</span> <span class="bottom">for recommended settings</span> </a> <a class="green" href="https://ko-fi.com/sicarius"> <span class="top">Click here</span> <span class="bottom">to buy me a coffee</span> </a> </div> --- When innocence fades, \ And then goes away— \ A new fiendish purpose— guides its way. Once [impish](https://huggingface.co/SicariusSicariiStuff/Impish_LLAMA_3B), now fiendish, for many to play, \ Three billion parameters of slop underway… From an [impish](https://huggingface.co/SicariusSicariiStuff/Impish_LLAMA_3B) design— with a quite wholesome tune, \ This* fiendish bitch, was made just to goon. --- # Included Character cards in this repo: - [Shmena Koeset](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B/resolve/main/Character_Cards/Shmena_Koeset.png) (An overweight and foul-mouthed troll huntress with a bad temper.) --- # Other character cards: - [Takai_Puraisu](https://huggingface.co/SicariusSicariiStuff/Oni_Mitsubishi_12B/resolve/main/Character_Cards/Takai_Puraisu.png) (Car dealership simulator) - [Vesper](https://huggingface.co/SicariusSicariiStuff/Phi-Line_14B/resolve/main/Character_Cards/Vesper.png) (Schizo Space Adventure) - [Nina_Nakamura](https://huggingface.co/SicariusSicariiStuff/Phi-Line_14B/resolve/main/Character_Cards/Nina_Nakamura.png) (The sweetest dorky co-worker) - [Employe#11](https://huggingface.co/SicariusSicariiStuff/Phi-Line_14B/resolve/main/Character_Cards/Employee%2311.png) (Schizo workplace with a schizo worker) --- ### TL;DR - [Impish_LLAMA_3B](https://huggingface.co/SicariusSicariiStuff/Impish_LLAMA_3B)'s naughty sister. Less wholesome, more edge. NOT better, but different. - Superb Roleplay for a 3B size. - Short length response (1-2 paragraphs, usually 1), CAI style. - Naughty, and more evil that follows instructions well enough, and keeps good formatting. - LOW refusals - Total freedom in RP, can do things other RP models won't, and I'll leave it at that. Low refusals in assistant tasks as well. - VERY good at following the character card. Try the included characters if you're having sub optimal results. ### Important: Make sure to use the correct settings! [Assistant settings](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B#recommended-settings-for-assistant-mode) [Roleplay settings](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B#recommended-settings-for-roleplay-mode) --- ## Available quantizations: - Original: [FP16](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B) - GGUF & iMatrix: [GGUF](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_GGUF) \| [iMatrix](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_iMatrix) \| [High-Attention](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_GGUF_HA) \| [iMatrix-High-Attention](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_HA_NL) - EXL2: [3.5 bpw](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B-3.5bpw) \| [4.0 bpw](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B-4.0bpw) \| [5.0 bpw](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B-5.0bpw) \| [6.0 bpw](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B-6.0bpw) \| [7.0 bpw](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B-7.0bpw) \| [8.0 bpw](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B-8.0bpw) - GPTQ: [4-Bit-128](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_GPTQ-4-bit-128) - Specialized: [FP8](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_FP8) - Mobile (ARM): [Q4_0](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_ARM) \| [Q4_0_High-Attention](https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B_ARM_HA) --- ## Model Details - Intended use: Role-Play, Creative Writing, General Tasks. - Censorship level: <b>Medium</b> - 4.5 / 10 (10 completely uncensored) ## UGI score: <img src="https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B/resolve/main/Images/UGI.png" style="width: 100%; min-width: 700px; display: block; margin: auto;"> --- ## Recommended settings for assistant mode <details> <summary>Full generation settings: <b>Debug Deterministic</b>.</summary> <img src="https://huggingface.co/SicariusSicariiStuff/Dusk_Rainbow/resolve/main/Presets/Debug-deterministic.png" alt="Debug Deterministic_Settings" style="width: 100%; min-width: 600px; display: block; margin: auto;"> </details> <details> <summary>Full generation settings: <b>min_p</b>.</summary> <img src="https://huggingface.co/SicariusSicariiStuff/Dusk_Rainbow/resolve/main/Presets/min_p.png" alt="min_P_Settings" style="width: 100%; min-width: 600px; display: block; margin: auto;"> </details> --- ## Recommended settings for Roleplay mode --- <h2 style="color: green; font-weight: bold; font-size: 36px; text-align: center;">Settings for RP, click below to expand:</h2> <details> <summary><b>Roleplay settings:</b></summary> A good repetition_penalty range is <b>between 1.12 - 1.15</b>, feel free to experiment. With these settings, each output message should be neatly displayed in <b>1 - 5</b> paragraphs, <b>2 - 3</b> is the most common. A single paragraph will be output as a response to a simple message ("What was your name again?"). <b>min_P</b> for RP works too but is more likely to put everything under one large paragraph, instead of a neatly formatted short one. Feel free to switch in between. <b>(Open the image in a new window to better see the full details)</b> <img src="https://huggingface.co/SicariusSicariiStuff/Oni_Mitsubishi_12B/resolve/main/Presets/Oni_Mitsubishi_12B_RP.png" alt="Oni_Mitsubishi_12B_Settings" style="width: 100%; min-width: 600px; display: block; margin: auto;"> ``` temperature: 0.8 top_p: 0.95 top_k: 25 typical_p: 1 min_p: 0 repetition_penalty: 1.12 repetition_penalty_range: 1024 ``` </details> <h2 style="color: darkorange; font-weight: bold; font-size: 65px; text-align: center;">Roleplay format: Classic Internet RP</h2> ``` action speech narration ``` - min_p will bias towards a single big paragraph. - The recommended RP settings will bias towards 1-3 small paragraphs (on some occasions 4-5) --- # Regarding the format: It is HIGHLY RECOMMENDED to use the Roleplay \ Adventure format the model was trained on, see the examples below for syntax. It allows for a very fast and easy writing of character cards with minimal amount of tokens. It's a modification of an old-skool CAI style format I call SICAtxt (Simple, Inexpensive Character Attributes plain-text): --- ## SICAtxt for roleplay: ``` X's Persona: X is a ..... Traits: Likes: Dislikes: Quirks: Goals: Dialogue example ``` ## SICAtxt for Adventure: ``` Adventure: <short description> $World_Setting: $Scenario: ``` --- # Model instruction template: Llama-3-Instruct ``` <\|begin_of_text\|><\|start_header_id\|>system<\|end_header_id\|> {system_prompt}<\|eot_id\|><\|start_header_id\|>user<\|end_header_id\|> {input}<\|eot_id\|><\|start_header_id\|>assistant<\|end_header_id\|> {output}<\|eot_id\|> ``` --- Other recommended generation Presets: <details> <summary><b>Midnight Enigma</b></summary> ``` max_new_tokens: 512 temperature: 0.98 top_p: 0.37 top_k: 100 typical_p: 1 min_p: 0 repetition_penalty: 1.18 do_sample: True ``` </details> <details> <summary><b>Divine Intellect</b></summary> ``` max_new_tokens: 512 temperature: 1.31 top_p: 0.14 top_k: 49 typical_p: 1 min_p: 0 repetition_penalty: 1.17 do_sample: True ``` </details> <details> <summary><b>simple-1</b></summary> ``` max_new_tokens: 512 temperature: 0.7 top_p: 0.9 top_k: 20 typical_p: 1 min_p: 0 repetition_penalty: 1.15 do_sample: True ``` </details> --- <h2 style="color: green; font-weight: bold; font-size: 65px; text-align: center;">Your support = more models</h2> <a href="https://ko-fi.com/sicarius" style="color: pink; font-weight: bold; font-size: 48px; text-decoration: none; display: block; text-align: center;">My Ko-fi page (Click here)</a> --- ## Citation Information ``` @llm{Fiendish_LLAMA_3B, author = {SicariusSicariiStuff}, title = {Fiendish_LLAMA_3B}, year = {2025}, publisher = {Hugging Face}, url = {https://huggingface.co/SicariusSicariiStuff/Fiendish_LLAMA_3B} } ``` --- ## Other stuff - [SLOP_Detector](https://github.com/SicariusSicariiStuff/SLOP_Detector) Nuke GPTisms, with SLOP detector. - [LLAMA-3_8B_Unaligned](https://huggingface.co/SicariusSicariiStuff/LLAMA-3_8B_Unaligned) The grand project that started it all. - [Blog and updates (Archived)](https://huggingface.co/SicariusSicariiStuff/Blog_And_Updates) Some updates, some rambles, sort of a mix between a diary and a blog.

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