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 |
|---|---|---|---|---|---|---|---|---|---|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756087806
|
kapalbalap
| 2025-08-25T02:11:05Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T02:10:59Z |
---
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).
|
ymatari/diffusion_so101_cleanup_table
|
ymatari
| 2025-08-25T02:09:24Z | 0 | 0 |
lerobot
|
[
"lerobot",
"safetensors",
"robotics",
"diffusion",
"dataset:ymatari/cleanup-table",
"arxiv:2303.04137",
"license:apache-2.0",
"region:us"
] |
robotics
| 2025-08-25T02:06:23Z |
---
datasets: ymatari/cleanup-table
library_name: lerobot
license: apache-2.0
model_name: diffusion
pipeline_tag: robotics
tags:
- lerobot
- robotics
- diffusion
---
# Model Card for diffusion
<!-- Provide a quick summary of what the model is/does. -->
[Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
See the full documentation at [LeRobot Docs](https://huggingface.co/docs/lerobot/index).
---
## How to Get Started with the Model
For a complete walkthrough, see the [training guide](https://huggingface.co/docs/lerobot/il_robots#train-a-policy).
Below is the short version on how to train and run inference/eval:
### Train from scratch
```bash
python -m lerobot.scripts.train \
--dataset.repo_id=${HF_USER}/<dataset> \
--policy.type=act \
--output_dir=outputs/train/<desired_policy_repo_id> \
--job_name=lerobot_training \
--policy.device=cuda \
--policy.repo_id=${HF_USER}/<desired_policy_repo_id>
--wandb.enable=true
```
_Writes checkpoints to `outputs/train/<desired_policy_repo_id>/checkpoints/`._
### Evaluate the policy/run inference
```bash
python -m lerobot.record \
--robot.type=so100_follower \
--dataset.repo_id=<hf_user>/eval_<dataset> \
--policy.path=<hf_user>/<desired_policy_repo_id> \
--episodes=10
```
Prefix the dataset repo with **eval\_** and supply `--policy.path` pointing to a local or hub checkpoint.
---
## Model Details
- **License:** apache-2.0
|
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756087352
|
IvanJAjebu
| 2025-08-25T02:03:43Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"thorny slender capybara",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T02:03:33Z |
---
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).
|
nema122/blockassist-bc-robust_fluffy_ram_1756087322
|
nema122
| 2025-08-25T02:03:16Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"robust fluffy ram",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T02:03:13Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- robust fluffy ram
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
vendi11/blockassist-bc-placid_placid_llama_1756087340
|
vendi11
| 2025-08-25T02:03:10Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"placid placid llama",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T02:03:07Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- placid placid llama
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756086981
|
IvanJAjebu
| 2025-08-25T01:57:30Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"thorny slender capybara",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:57:21Z |
---
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).
|
liukevin666/blockassist-bc-yawning_striped_cassowary_1756086616
|
liukevin666
| 2025-08-25T01:53:05Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"yawning striped cassowary",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:51:17Z |
---
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).
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756086669
|
kapalbalap
| 2025-08-25T01:51:54Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:51:48Z |
---
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).
|
copiglet/medgemma-4b-it-sft-lora-amc-n-abn-test
|
copiglet
| 2025-08-25T01:51:00Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"sft",
"endpoints_compatible",
"region:us"
] | null | 2025-08-16T19:06:52Z |
---
library_name: transformers
model_name: medgemma-4b-it-sft-lora-amc-n-abn-test
tags:
- generated_from_trainer
- trl
- sft
licence: license
---
# Model Card for medgemma-4b-it-sft-lora-amc-n-abn-test
This model is a fine-tuned version of [None](https://huggingface.co/None).
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="copiglet/medgemma-4b-it-sft-lora-amc-n-abn-test", 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 SFT.
### Framework versions
- TRL: 0.21.0
- Transformers: 4.55.2
- Pytorch: 2.6.0+cu124
- 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}}
}
```
|
vendi11/blockassist-bc-placid_placid_llama_1756086558
|
vendi11
| 2025-08-25T01:50:06Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"placid placid llama",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:50:04Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- placid placid llama
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
fujiantiiazhraa/blockassist-bc-marine_robust_bee_1756085082
|
fujiantiiazhraa
| 2025-08-25T01:49:35Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"marine robust bee",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:49:31Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- marine robust bee
---
# 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_1756084881
|
unitova
| 2025-08-25T01:49:04Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"zealous sneaky raven",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:49:00Z |
---
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).
|
zuruyu/blockassist-bc-endangered_pesty_chinchilla_1756086388
|
zuruyu
| 2025-08-25T01:48:29Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"endangered pesty chinchilla",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:47:24Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- endangered pesty chinchilla
---
# 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_1756085303
|
Sayemahsjn
| 2025-08-25T01:48:02Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"playful feline octopus",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:47:57Z |
---
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).
|
aleebaster/blockassist-bc-sly_eager_boar_1756084843
|
aleebaster
| 2025-08-25T01:47:23Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"sly eager boar",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:47:15Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- sly eager boar
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
moppiop/blockassist-bc-foxy_reclusive_bear_1756086178
|
moppiop
| 2025-08-25T01:43:34Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"foxy reclusive bear",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:43:00Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- foxy reclusive bear
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Gemneye/Trystan
|
Gemneye
| 2025-08-25T01:43:23Z | 0 | 0 |
diffusers
|
[
"diffusers",
"text-to-image",
"lora",
"template:diffusion-lora",
"base_model:Qwen/Qwen-Image",
"base_model:adapter:Qwen/Qwen-Image",
"license:apache-2.0",
"region:us"
] |
text-to-image
| 2025-08-25T01:38:52Z |
---
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/Trystan.png
text: >-
Tryst@n a man, white background, medium shot, modeling clothing, studio
lighting, white backdrop
base_model: Qwen/Qwen-Image
instance_prompt: Tryst@n
license: apache-2.0
---
# Trystan
<Gallery />
## Model description
Trained on AI toolkit
## Trigger words
You should use `Tryst@n` to trigger the image generation.
## Download model
[Download](/Gemneye/Trystan/tree/main) them in the Files & versions tab.
|
nema122/blockassist-bc-robust_fluffy_ram_1756086000
|
nema122
| 2025-08-25T01:41:14Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"robust fluffy ram",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:41:12Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- robust fluffy ram
---
# 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_1756085955
|
liukevin666
| 2025-08-25T01:40:50Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"yawning striped cassowary",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:40:15Z |
---
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).
|
kojeklollipop/blockassist-bc-spotted_amphibious_stork_1756084399
|
kojeklollipop
| 2025-08-25T01:40:00Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"spotted amphibious stork",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:39:55Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- spotted amphibious stork
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
BootesVoid/cme2zy5nd010e6aq1g1cjj0c8_cmeqemtfj0bektlqbr3uz8amx
|
BootesVoid
| 2025-08-25T01:35:12Z | 0 | 0 |
diffusers
|
[
"diffusers",
"flux",
"lora",
"replicate",
"text-to-image",
"en",
"base_model:black-forest-labs/FLUX.1-dev",
"base_model:adapter:black-forest-labs/FLUX.1-dev",
"license:other",
"region:us"
] |
text-to-image
| 2025-08-25T01:35:11Z |
---
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
language:
- en
tags:
- flux
- diffusers
- lora
- replicate
base_model: "black-forest-labs/FLUX.1-dev"
pipeline_tag: text-to-image
# widget:
# - text: >-
# prompt
# output:
# url: https://...
instance_prompt: MIDGET
---
# Cme2Zy5Nd010E6Aq1G1Cjj0C8_Cmeqemtfj0Bektlqbr3Uz8Amx
<Gallery />
## About this LoRA
This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer/train
## Trigger words
You should use `MIDGET` to trigger the image generation.
## Run this LoRA with an API using Replicate
```py
import replicate
input = {
"prompt": "MIDGET",
"lora_weights": "https://huggingface.co/BootesVoid/cme2zy5nd010e6aq1g1cjj0c8_cmeqemtfj0bektlqbr3uz8amx/resolve/main/lora.safetensors"
}
output = replicate.run(
"black-forest-labs/flux-dev-lora",
input=input
)
for index, item in enumerate(output):
with open(f"output_{index}.webp", "wb") as file:
file.write(item.read())
```
## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
```py
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('BootesVoid/cme2zy5nd010e6aq1g1cjj0c8_cmeqemtfj0bektlqbr3uz8amx', weight_name='lora.safetensors')
image = pipeline('MIDGET').images[0]
```
For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
## Training details
- Steps: 2500
- Learning rate: 9e-05
- LoRA rank: 16
## Contribute your own examples
You can use the [community tab](https://huggingface.co/BootesVoid/cme2zy5nd010e6aq1g1cjj0c8_cmeqemtfj0bektlqbr3uz8amx/discussions) to add images that show off what you’ve made with this LoRA.
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756085591
|
kapalbalap
| 2025-08-25T01:34:06Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:34:01Z |
---
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).
|
nightmedia/Cerium-Qwen3-R1-Dev-qx6-hi-mlx
|
nightmedia
| 2025-08-25T01:28:33Z | 0 | 0 |
mlx
|
[
"mlx",
"safetensors",
"qwen3",
"moe",
"trl",
"text-generation-inference",
"code",
"math",
"science",
"text-generation",
"conversational",
"en",
"base_model:prithivMLmods/Cerium-Qwen3-R1-Dev",
"base_model:quantized:prithivMLmods/Cerium-Qwen3-R1-Dev",
"license:apache-2.0",
"6-bit",
"region:us"
] |
text-generation
| 2025-08-25T01:27:45Z |
---
license: apache-2.0
language:
- en
library_name: mlx
base_model: prithivMLmods/Cerium-Qwen3-R1-Dev
pipeline_tag: text-generation
tags:
- moe
- trl
- text-generation-inference
- code
- math
- science
- mlx
---
# Cerium-Qwen3-R1-Dev-qx6-hi-mlx
This model [Cerium-Qwen3-R1-Dev-qx6-hi-mlx](https://huggingface.co/Cerium-Qwen3-R1-Dev-qx6-hi-mlx) was
converted to MLX format from [prithivMLmods/Cerium-Qwen3-R1-Dev](https://huggingface.co/prithivMLmods/Cerium-Qwen3-R1-Dev)
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("Cerium-Qwen3-R1-Dev-qx6-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)
```
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756085154
|
kapalbalap
| 2025-08-25T01:26:39Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:26:32Z |
---
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).
|
nekusu/faster-whisper-large-v3-turbo-latam-int8-ct2
|
nekusu
| 2025-08-25T01:26:31Z | 0 | 0 | null |
[
"whisper",
"faster-whisper",
"ctranslate2",
"stt",
"audio",
"voice",
"8-bit",
"automatic-speech-recognition",
"es",
"base_model:marianbasti/whisper-large-v3-turbo-latam",
"base_model:quantized:marianbasti/whisper-large-v3-turbo-latam",
"license:mit",
"region:us"
] |
automatic-speech-recognition
| 2025-08-25T00:45:00Z |
---
license: mit
language:
- es
base_model:
- marianbasti/whisper-large-v3-turbo-latam
base_model_relation: quantized
pipeline_tag: automatic-speech-recognition
tags:
- whisper
- faster-whisper
- ctranslate2
- stt
- audio
- voice
- 8-bit
---
# CTranslate2 Conversion of whisper-large-v3-turbo-latam (INT8 Quantization)
This model is converted from [marianbasti/whisper-large-v3-turbo-latam](https://huggingface.co/marianbasti/whisper-large-v3-turbo-latam) to the CTranslate2 format using INT8 quantization, primarily for use with [faster-whisper](https://github.com/SYSTRAN/faster-whisper).
## Model Details
For more details about the finetuned model, see its original [model card](https://huggingface.co/marianbasti/whisper-large-v3-turbo-latam).
## Conversion Details
The original model was converted using the following command:
```
ct2-transformers-converter --model marianbasti/whisper-large-v3-turbo-latam --copy_files tokenizer.json preprocessor_config.json --output_dir faster-whisper-large-v3-turbo-latam-int8-ct2 --quantization int8
```
More info on [model conversion](https://github.com/SYSTRAN/faster-whisper#model-conversion).
Check [Zoont/faster-whisper-large-v3-turbo-int8-ct2](https://huggingface.co/Zoont/faster-whisper-large-v3-turbo-int8-ct2) for a quantized version of the original [whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo).
|
nightmedia/Cerium-Qwen3-R1-Dev-q8-hi-mlx
|
nightmedia
| 2025-08-25T01:22:11Z | 0 | 0 |
mlx
|
[
"mlx",
"safetensors",
"qwen3",
"moe",
"trl",
"text-generation-inference",
"code",
"math",
"science",
"text-generation",
"conversational",
"en",
"base_model:prithivMLmods/Cerium-Qwen3-R1-Dev",
"base_model:quantized:prithivMLmods/Cerium-Qwen3-R1-Dev",
"license:apache-2.0",
"8-bit",
"region:us"
] |
text-generation
| 2025-08-25T01:17:26Z |
---
license: apache-2.0
language:
- en
library_name: mlx
base_model: prithivMLmods/Cerium-Qwen3-R1-Dev
pipeline_tag: text-generation
tags:
- moe
- trl
- text-generation-inference
- code
- math
- science
- mlx
---
# Cerium-Qwen3-R1-Dev-q8-hi-mlx
This model [Cerium-Qwen3-R1-Dev-q8-hi-mlx](https://huggingface.co/Cerium-Qwen3-R1-Dev-q8-hi-mlx) was
converted to MLX format from [prithivMLmods/Cerium-Qwen3-R1-Dev](https://huggingface.co/prithivMLmods/Cerium-Qwen3-R1-Dev)
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("Cerium-Qwen3-R1-Dev-q8-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)
```
|
TheDrummer/Cydonia-24B-v4.1-GGUF
|
TheDrummer
| 2025-08-25T01:21:41Z | 7,858 | 17 | null |
[
"gguf",
"endpoints_compatible",
"region:us",
"conversational"
] | null | 2025-08-17T10:23:58Z |
---
base_model:
- mistralai/Mistral-Small-3.2-24B-Instruct-2507
---
# Join our Discord! https://discord.gg/BeaverAI
## Nearly 7000 members strong 💪 A hub for users and makers alike!
---
## Drummer is open for work / employment (I'm a Software Engineer). Contact me through any of these channels: https://linktr.ee/thelocaldrummer
### Thank you to everyone who subscribed through [Patreon](https://www.patreon.com/TheDrummer). Your suppprt helps me chug along in this brave new world.
---
[Drummer](https://huggingface.co/TheDrummer) proudly presents...
# Cydonia 24B v4.1 💿
## Usage
- Mistral v7 Tekken
## Description
> Cydonia Evolved again.
> I have to praise this model for good focus. I said earlier that it still remembers it at 12K. I think my personal evaluation has it already beaten the rest.
> Damn okay this model is actually pretty good. I don't have enough vram to test it on longer chats to 16k, but on 6k chats it's looking good and without deepseek's slop.
> Wow, for a 24B this thing has some writing chops. Like it nails mood and nuance and shit with the prose, descriptive but not purple prose. you may have cracked the Cydonias for good with this one. The more I play with it, the more it feels like a level up from the prior ones. Haven't got into long context yet though. My cards tend to favor the opposite or at best neutral. Its rolling with the card, and nailing it, its a bit fallen and its doing good prose to match. Yeah this one's a banger.
> Very good. For 24B, the best I've come across. Like even swipes, it stays creative and writes just as well as the swipes before it but doesn't recycle anything from them. It doesn't go overboard on the creativity like Gemma can do, it'll write what you tell it or if RP pick up on things pretty accurately. The prose isn't purple either, it's good.
> I dunno how you have broken the spell R1 Cydonia had on me or what made me try this on a whim but you have gold on your hands with this tune. Again.
> it really doesn't feel like a mistral tune which is honestly the best compliment I can give it. I'm not getting the usual mistral tuneisms from it.
> It's probably the best Cydonia.
## Links
- Original: https://huggingface.co/TheDrummer/Cydonia-24B-v4.1
- GGUF: https://huggingface.co/TheDrummer/Cydonia-24B-v4.1-GGUF
- iMatrix (recommended): https://huggingface.co/bartowski/TheDrummer_Cydonia-24B-v4.1-GGUF
- EXL3: https://huggingface.co/ArtusDev/TheDrummer_Cydonia-24B-v4.1-EXL3
## Special Thanks
Hoping to make SleepDeprived proud with this one. RIP.
`config-v4j`
|
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756084829
|
IvanJAjebu
| 2025-08-25T01:21:36Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"thorny slender capybara",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:21:28Z |
---
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).
|
cixzer/blockassist-bc-gregarious_long_cheetah_1756084659
|
cixzer
| 2025-08-25T01:20:45Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"gregarious long cheetah",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:20:08Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- gregarious long cheetah
---
# 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_1756084729
|
kapalbalap
| 2025-08-25T01:19:46Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:19:40Z |
---
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).
|
liukevin666/blockassist-bc-yawning_striped_cassowary_1756084632
|
liukevin666
| 2025-08-25T01:19:37Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"yawning striped cassowary",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:18:14Z |
---
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).
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1756084501
|
Dejiat
| 2025-08-25T01:15:29Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:15:26Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
mesh-labs/v0.1-2x2-stage003
|
mesh-labs
| 2025-08-25T01:15:17Z | 0 | 1 | null |
[
"safetensors",
"mesh",
"moe",
"mesh-labs",
"alpha",
"preview",
"research",
"experiment",
"routing",
"innovative",
"innovation",
"mesh-moe",
"custom_code",
"text-generation",
"conversational",
"en",
"dataset:HuggingFaceFW/fineweb-edu",
"dataset:HuggingFaceH4/MATH-500",
"dataset:openai/gsm8k",
"license:apache-2.0",
"region:us"
] |
text-generation
| 2025-08-25T00:50:23Z |
---
license: apache-2.0
datasets:
- HuggingFaceFW/fineweb-edu
- HuggingFaceH4/MATH-500
- openai/gsm8k
language:
- en
pipeline_tag: text-generation
tags:
- mesh
- moe
- mesh-labs
- alpha
- preview
- research
- experiment
- routing
- innovative
- innovation
- mesh-moe
- custom_code
---
# Mesh-v0.1-2x2 (Stage 003)
## Introducing mesh
This is our first ever model! Allow us to explain how the `mesh` architecture works in detail.
- Neural Mesh extends the concept of Mixture of Experts by allowing bidirectional expert communication.
- The experts are shared in a bidimensional grid (2x2, 4x4, etc.) layout, that allows for them to communicate with their neighbors using the "Neighbor Exchange" method.
- Just like MoE models, Mesh models have dynamic routing, and through the `routing_k` parameter you can define the amount of active parameters. For this model (2x2):
- top-1 routing: 173M active parameters
- top-2 routing: 242M active parameters (default)
- dense routing: 302M active parameters
## Here's how the mesh architecture works:
## How to load the model
```python
from transformers import AutoModelForCausalLM, AutoTokenizer, AutoConfig, PretrainedConfig, PreTrainedModel
import torch
import torch.nn as nn
import torch.nn.functional as F
import math
from transformers.modeling_outputs import CausalLMOutputWithPast
from transformers.generation import GenerationMixin
import os
class MeshConfig(PretrainedConfig):
model_type = "mesh"
def __init__(
self,
vocab_size=32000,
hidden_size=768,
intermediate_size=2048,
num_hidden_layers=12,
num_attention_heads=12,
num_key_value_heads=12,
max_position_embeddings=4096,
initializer_range=0.02,
rms_norm_eps=1e-6,
use_cache=True,
pad_token_id=0,
bos_token_id=1,
eos_token_id=2,
tie_word_embeddings=False,
mesh_grid_size=(2, 2),
expert_intermediate_size=256,
routing_k=2,
neighbor_exchange_enabled=True,
cross_expert_attention_enabled=True,
expert_scale_factor="sqrt_k",
load_in_8bit=False,
load_in_4bit=False,
**kwargs
):
super().__init__(
vocab_size=vocab_size,
hidden_size=hidden_size,
intermediate_size=intermediate_size,
num_hidden_layers=num_hidden_layers,
num_attention_heads=num_attention_heads,
num_key_value_heads=num_key_value_heads,
max_position_embeddings=max_position_embeddings,
initializer_range=initializer_range,
rms_norm_eps=rms_norm_eps,
use_cache=use_cache,
pad_token_id=pad_token_id,
bos_token_id=bos_token_id,
eos_token_id=eos_token_id,
tie_word_embeddings=tie_word_embeddings,
**kwargs,
)
self.mesh_grid_size = mesh_grid_size
self.expert_intermediate_size = kwargs.pop("expert_intermediate_size", intermediate_size // (mesh_grid_size[0] * mesh_grid_size[1]))
self.routing_k = routing_k
self.neighbor_exchange_enabled = neighbor_exchange_enabled
self.cross_expert_attention_enabled = cross_expert_attention_enabled
self.expert_scale_factor = expert_scale_factor
self.load_in_8bit = load_in_8bit
self.load_in_4bit = load_in_4bit
class MeshExpert(nn.Module):
def __init__(self, config: MeshConfig):
super().__init__()
self.fc1 = nn.Linear(config.hidden_size, config.expert_intermediate_size)
self.gelu = nn.GELU()
self.fc2 = nn.Linear(config.expert_intermediate_size, config.hidden_size)
def forward(self, x):
return self.fc2(self.gelu(self.fc1(x)))
class MeshRouter(nn.Module):
def __init__(self, config: MeshConfig):
super().__init__()
self.gate = nn.Linear(config.hidden_size, config.mesh_grid_size[0] * config.mesh_grid_size[1])
self.softmax = nn.Softmax(dim=-1)
self.routing_k = config.routing_k
def forward(self, x):
gate_scores = self.gate(x)
gate_weights = self.softmax(gate_scores)
topk_weights, topk_indices = torch.topk(gate_weights, self.routing_k, dim=-1)
return topk_weights, topk_indices
class NeighborExchange(nn.Module):
def __init__(self, config: MeshConfig):
super().__init__()
self.config = config
self.num_experts_x = config.mesh_grid_size[0]
self.num_experts_y = config.mesh_grid_size[1]
self.num_experts = self.num_experts_x * self.num_experts_y
self.exchange_projection = nn.Linear(config.hidden_size, config.hidden_size)
def forward(self, expert_outputs, expert_indices=None):
if not self.config.neighbor_exchange_enabled:
return expert_outputs
batch_size, seq_length, num_experts, hidden_size = expert_outputs.shape
reshaped_outputs = expert_outputs.view(batch_size, seq_length, self.num_experts_x, self.num_experts_y, hidden_size)
aggregated_neighbor_info = torch.zeros_like(reshaped_outputs)
for i in range(self.num_experts_x):
for j in range(self.num_experts_y):
current_expert_output = reshaped_outputs[:, :, i, j, :]
neighbor_info = torch.zeros_like(current_expert_output)
neighbors = []
if i > 0: neighbors.append(reshaped_outputs[:, :, i-1, j, :])
if i < self.num_experts_x - 1: neighbors.append(reshaped_outputs[:, :, i+1, j, :])
if j > 0: neighbors.append(reshaped_outputs[:, :, i, j-1, :])
if j < self.num_experts_y - 1: neighbors.append(reshaped_outputs[:, :, i, j+1, :])
if neighbors:
neighbor_stack = torch.stack(neighbors, dim=-2)
aggregated_info = torch.mean(neighbor_stack, dim=-2)
neighbor_info = aggregated_info
transformed_neighbor_info = self.exchange_projection(neighbor_info)
aggregated_neighbor_info[:, :, i, j, :] = transformed_neighbor_info
aggregated_neighbor_info = aggregated_neighbor_info.view(batch_size, seq_length, num_experts, hidden_size)
exchanged_expert_outputs = expert_outputs + aggregated_neighbor_info
return exchanged_expert_outputs
class CrossExpertAttention(nn.Module):
def __init__(self, config: MeshConfig):
super().__init__()
self.config = config
self.cross_attention = nn.MultiheadAttention(
embed_dim=config.hidden_size,
num_heads=config.num_attention_heads,
batch_first=True
)
def forward(self, expert_outputs):
if not self.config.cross_expert_attention_enabled:
return expert_outputs
batch_seq_size = expert_outputs.shape[0] * expert_outputs.shape[1]
reshaped_outputs = expert_outputs.view(batch_seq_size, self.config.mesh_grid_size[0] * self.config.mesh_grid_size[1], self.config.hidden_size)
cross_attn_output, _ = self.cross_attention(reshaped_outputs, reshaped_outputs, reshaped_outputs)
cross_attn_output = cross_attn_output.view(
expert_outputs.shape[0], expert_outputs.shape[1], self.config.mesh_grid_size[0] * self.config.mesh_grid_size[1], self.config.hidden_size
)
return cross_attn_output
class MeshLayer(nn.Module):
def __init__(self, config: MeshConfig):
super().__init__()
self.config = config
self.router = MeshRouter(config)
self.experts = nn.ModuleList([MeshExpert(config) for _ in range(config.mesh_grid_size[0] * config.mesh_grid_size[1])])
self.neighbor_exchange = NeighborExchange(config)
self.cross_expert_attention = CrossExpertAttention(config)
def forward(self, hidden_states):
topk_weights, topk_indices = self.router(hidden_states)
expanded_hidden_states = hidden_states.unsqueeze(2).expand(-1, -1, self.config.mesh_grid_size[0] * self.config.mesh_grid_size[1], -1)
if self.config.expert_scale_factor == "sqrt_k":
scaling_factor = math.sqrt(self.config.routing_k)
scaled_expert_inputs = expanded_hidden_states * scaling_factor
elif self.config.expert_scale_factor == "1_over_k":
scaling_factor = 1.0 / self.config.routing_k
scaled_expert_inputs = expanded_hidden_states * scaling_factor
else:
scaled_expert_inputs = expanded_hidden_states
expert_outputs_list = [expert(scaled_expert_inputs[:, :, i, :]) for i, expert in enumerate(self.experts)]
expert_outputs = torch.stack(expert_outputs_list, dim=2)
exchanged_expert_outputs = self.neighbor_exchange(expert_outputs, topk_indices)
cross_attned_expert_outputs = self.cross_expert_attention(exchanged_expert_outputs)
gathered_outputs = torch.gather(
cross_attned_expert_outputs,
dim=2,
index=topk_indices.unsqueeze(-1).expand(-1, -1, -1, self.config.hidden_size)
)
combined_output = (gathered_outputs * topk_weights.unsqueeze(-1)).sum(dim=2)
return combined_output, topk_indices
class MeshModel(PreTrainedModel, GenerationMixin):
config_class = MeshConfig
def __init__(self, config: MeshConfig):
super().__init__(config)
self.config = config
self.embedding = nn.Embedding(config.vocab_size, config.hidden_size)
self.layers = nn.ModuleList([MeshLayer(config) for _ in range(config.num_hidden_layers)])
self.norm = nn.LayerNorm(config.hidden_size, eps=config.rms_norm_eps)
self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
self.post_init()
self._supports_gradient_checkpointing = True
self.gradient_checkpointing = False
def forward(
self,
input_ids=None,
attention_mask=None,
token_type_ids=None,
position_ids=None,
inputs_embeds=None,
labels=None,
return_dict=None,
output_attentions=None,
output_hidden_states=None,
past_key_values=None,
):
return_dict = return_dict if return_dict is not None else self.config.use_return_dict
if input_ids is not None and inputs_embeds is not None:
raise ValueError("You cannot specify both input_ids and inputs_embeds at the same time")
elif input_ids is not None:
inputs_embeds = self.embedding(input_ids)
elif inputs_embeds is not None:
pass
else:
raise ValueError("You have to specify either input_ids or inputs_embeds")
hidden_states = inputs_embeds
if self.gradient_checkpointing and self.training:
import torch.utils.checkpoint
for i, layer in enumerate(self.layers):
if hasattr(layer, 'forward') and callable(layer.forward):
if self.gradient_checkpointing and self.training:
checkpoint_output = torch.utils.checkpoint.checkpoint(
layer, hidden_states, use_reentrant=False
)
if isinstance(checkpoint_output, tuple):
hidden_states = checkpoint_output[0]
else:
hidden_states = checkpoint_output
else:
layer_output = layer(hidden_states)
hidden_states = layer_output[0]
else:
print(f"Warning: Layer {i} does not have a callable forward method. Skipping layer processing.")
hidden_states = self.norm(hidden_states)
logits = self.lm_head(hidden_states)
loss = None
if labels is not None:
loss_fct = nn.CrossEntropyLoss()
shift_logits = logits[..., :-1, :].contiguous()
shift_labels = labels[..., 1:].contiguous()
loss = loss_fct(shift_logits.view(-1, self.config.vocab_size), shift_labels.view(-1))
if return_dict:
return CausalLMOutputWithPast(
loss=loss,
logits=logits,
)
else:
return (loss, logits)
def prepare_inputs_for_generation(self, input_ids, past_key_values=None, inputs_embeds=None, **kwargs):
if past_key_values is not None:
input_ids = input_ids[:, -1].unsqueeze(-1)
if inputs_embeds is not None:
inputs_embeds = inputs_embeds[:, -1, :].unsqueeze(1)
if inputs_embeds is not None:
model_inputs = {"inputs_embeds": inputs_embeds}
else:
model_inputs = {"input_ids": input_ids}
if "attention_mask" in kwargs:
model_inputs["attention_mask"] = kwargs["attention_mask"]
return model_inputs
def gradient_checkpointing_enable(self, gradient_checkpointing_kwargs=None):
self.gradient_checkpointing = True
self.config.gradient_checkpointing = True
print("Gradient checkpointing enabled on MeshModel.")
def gradient_checkpointing_disable(self):
self.gradient_checkpointing = False
self.config.gradient_checkpointing = False
print("Gradient checkpointing disabled on MeshModel.")
def _set_gradient_checkpointing(self, enable=True):
if enable:
self.gradient_checkpointing_enable()
else:
self.gradient_checkpointing_disable()
from transformers import AutoConfig
AutoConfig.register("mesh", MeshConfig)
AutoModelForCausalLM.register(MeshConfig, MeshModel)
HF_MERGED_REPO_STAGE003 = "mesh-labs/v0.1-2x2-stage003"
loaded_model_stage003 = None
loaded_tokenizer_stage003 = None
try:
print(f"Attempting to load Stage 003 merged model from HF: {HF_MERGED_REPO_STAGE003}...")
device_map = "auto"
loaded_model_stage003 = AutoModelForCausalLM.from_pretrained(
HF_MERGED_REPO_STAGE003,
trust_remote_code=True,
device_map=device_map,
torch_dtype=torch.float32
)
if torch.cuda.is_available():
loaded_model_stage003.to('cuda')
print("Stage 003 merged model moved to GPU.")
else:
print("Stage 003 merged model loaded on CPU.")
loaded_tokenizer_stage003 = AutoTokenizer.from_pretrained(
HF_MERGED_REPO_STAGE003,
trust_remote_code=True,
use_fast=False
)
print("Stage 003 merged model and tokenizer loaded successfully from Hugging Face Hub.")
except Exception as e:
print(f"Error loading Stage 003 merged model or tokenizer from Hugging Face Hub: {e}")
loaded_model_stage003 = None
loaded_tokenizer_stage003 = None
if loaded_model_stage003 is not None and loaded_tokenizer_stage003 is not None:
print("\n--- Starting Chat Interface ---")
print("Type your message and press Enter. Type 'quit' to exit.")
loaded_model_stage003.eval()
while True:
try:
user_input = input("You: ")
if user_input.lower() == 'quit':
break
prompt = f"Question: {user_input}\nAnswer:"
inputs = loaded_tokenizer_stage003(prompt, return_tensors="pt")
if torch.cuda.is_available():
inputs = {k: v.to('cuda') for k, v in inputs.items()}
with torch.no_grad():
outputs = loaded_model_stage003.generate(
**inputs,
max_new_tokens=128,
num_beams=1,
do_sample=False,
)
generated_sequence = loaded_tokenizer_stage003.decode(outputs[0], skip_special_tokens=True)
answer_prefix = "Answer:"
answer_start_index = generated_sequence.find(answer_prefix)
if answer_start_index != -1:
generated_answer = generated_sequence[answer_start_index + len(answer_prefix):].strip()
else:
print("Warning: 'Answer:' prefix not found in generated text. Showing full generated sequence.")
generated_answer = generated_sequence.strip()
print("Model:", generated_answer)
except Exception as e:
print(f"An error occurred: {e}")
print("Please try again or type 'quit' to exit.")
else:
print("\nModel or tokenizer not loaded. Cannot start chat interface.")
```
## Disclaimer
This small language model is just a proof-of-concept, paving the way to the final release, which is likely to happen in Q4 2025, and include more models and better support from external libraries such as Transformers and Llama.cpp.
|
Sayemahsjn/blockassist-bc-playful_feline_octopus_1756083401
|
Sayemahsjn
| 2025-08-25T01:15:11Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"playful feline octopus",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:15:06Z |
---
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).
|
nqdhocai/LegalGemma-3-1b-it
|
nqdhocai
| 2025-08-25T01:14:25Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"gemma3_text",
"text-generation",
"text-generation-inference",
"unsloth",
"conversational",
"en",
"base_model:unsloth/gemma-3-1b-it",
"base_model:finetune:unsloth/gemma-3-1b-it",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"region:us"
] |
text-generation
| 2025-08-25T01:13:23Z |
---
base_model: unsloth/gemma-3-1b-it
tags:
- text-generation-inference
- transformers
- unsloth
- gemma3_text
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** nqdhocai
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gemma-3-1b-it
This gemma3_text model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756084389
|
kapalbalap
| 2025-08-25T01:14:08Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:14:02Z |
---
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).
|
xinyifang/ArxivGPT
|
xinyifang
| 2025-08-25T01:11:51Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"gpt_oss",
"text-generation",
"text-generation-inference",
"unsloth",
"conversational",
"en",
"base_model:unsloth/gpt-oss-20b-unsloth-bnb-4bit",
"base_model:finetune:unsloth/gpt-oss-20b-unsloth-bnb-4bit",
"license:apache-2.0",
"autotrain_compatible",
"endpoints_compatible",
"8-bit",
"region:us"
] |
text-generation
| 2025-08-25T00:59:18Z |
---
base_model: unsloth/gpt-oss-20b-unsloth-bnb-4bit
tags:
- text-generation-inference
- transformers
- unsloth
- gpt_oss
license: apache-2.0
language:
- en
---
# Uploaded finetuned model
- **Developed by:** xinyifang
- **License:** apache-2.0
- **Finetuned from model :** unsloth/gpt-oss-20b-unsloth-bnb-4bit
This gpt_oss model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
|
coelacanthxyz/blockassist-bc-finicky_thriving_grouse_1756082662
|
coelacanthxyz
| 2025-08-25T01:11:29Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"finicky thriving grouse",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:11:22Z |
---
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).
|
roeker/blockassist-bc-quick_wiry_owl_1756084211
|
roeker
| 2025-08-25T01:11:27Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"quick wiry owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:10:51Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- quick wiry 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_1756084080
|
kapalbalap
| 2025-08-25T01:08:48Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T01:08:34Z |
---
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).
|
roeker/blockassist-bc-quick_wiry_owl_1756083527
|
roeker
| 2025-08-25T01:00:05Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"quick wiry owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:59:29Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- quick wiry 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_1756083456
|
kapalbalap
| 2025-08-25T00:58:27Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:58:21Z |
---
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).
|
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756083330
|
IvanJAjebu
| 2025-08-25T00:56:41Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"thorny slender capybara",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:56:32Z |
---
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).
|
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756083040
|
IvanJAjebu
| 2025-08-25T00:51:41Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"thorny slender capybara",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:51:32Z |
---
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).
|
neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_prover0_1_0_iter_3_prover0_175608
|
neural-interactive-proofs
| 2025-08-25T00:51:16Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"trl",
"dpo",
"arxiv:2305.18290",
"base_model:Qwen/Qwen2.5-32B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-32B-Instruct",
"endpoints_compatible",
"region:us"
] | null | 2025-08-25T00:50:36Z |
---
base_model: Qwen/Qwen2.5-32B-Instruct
library_name: transformers
model_name: finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_prover0_1_0_iter_3_prover0_175608
tags:
- generated_from_trainer
- trl
- dpo
licence: license
---
# Model Card for finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_prover0_1_0_iter_3_prover0_175608
This model is a fine-tuned version of [Qwen/Qwen2.5-32B-Instruct](https://huggingface.co/Qwen/Qwen2.5-32B-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="neural-interactive-proofs/finetune_dpo_qwen2_5-32b-instruct_cv_qwen2.5_32B_prover_debate_prover0_1_0_iter_3_prover0_175608", 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/lrhammond-team/pvg-self-hosted-finetune/runs/qwen2_5-32b-instruct_dpo_2025-08-25_01-29-53_cv_qwen2.5_32B_prover_debate_prover0_1_0_iter_3_prover0)
This model was trained with DPO, a method introduced in [Direct Preference Optimization: Your Language Model is Secretly a Reward Model](https://huggingface.co/papers/2305.18290).
### Framework versions
- TRL: 0.18.2
- Transformers: 4.53.2
- Pytorch: 2.7.0
- Datasets: 3.0.0
- Tokenizers: 0.21.1
## Citations
Cite DPO as:
```bibtex
@inproceedings{rafailov2023direct,
title = {{Direct Preference Optimization: Your Language Model is Secretly a Reward Model}},
author = {Rafael Rafailov and Archit Sharma and Eric Mitchell and Christopher D. Manning and Stefano Ermon and Chelsea Finn},
year = 2023,
booktitle = {Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023, New Orleans, LA, USA, December 10 - 16, 2023},
url = {http://papers.nips.cc/paper_files/paper/2023/hash/a85b405ed65c6477a4fe8302b5e06ce7-Abstract-Conference.html},
editor = {Alice Oh and Tristan Naumann and Amir Globerson and Kate Saenko and Moritz Hardt and Sergey Levine},
}
```
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}}
}
```
|
indoempatnol/blockassist-bc-fishy_wary_swan_1756081247
|
indoempatnol
| 2025-08-25T00:48:14Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"fishy wary swan",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:48:10Z |
---
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).
|
vendi11/blockassist-bc-placid_placid_llama_1756082820
|
vendi11
| 2025-08-25T00:47:50Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"placid placid llama",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:47:47Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- placid placid llama
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
helmutsukocok/blockassist-bc-loud_scavenging_kangaroo_1756081353
|
helmutsukocok
| 2025-08-25T00:47:20Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"loud scavenging kangaroo",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:47:16Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- loud scavenging kangaroo
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
nightmedia/QiMing-Holos-Plus-Qwen3-8B-q6-hi-mlx
|
nightmedia
| 2025-08-25T00:46:55Z | 0 | 0 |
mlx
|
[
"mlx",
"safetensors",
"qwen3",
"qwen",
"unsloth",
"qiming",
"qiming-holos",
"bagua",
"decision-making",
"strategic-analysis",
"cognitive-architecture",
"chat",
"lora",
"philosophy-driven-ai",
"text-generation",
"conversational",
"zh",
"en",
"base_model:aifeifei798/QiMing-Holos-Plus-Qwen3-8B",
"base_model:adapter:aifeifei798/QiMing-Holos-Plus-Qwen3-8B",
"license:apache-2.0",
"6-bit",
"region:us"
] |
text-generation
| 2025-08-25T00:43:00Z |
---
license: apache-2.0
language:
- zh
- en
tags:
- qwen
- qwen3
- unsloth
- qiming
- qiming-holos
- bagua
- decision-making
- strategic-analysis
- cognitive-architecture
- chat
- lora
- philosophy-driven-ai
- mlx
pipeline_tag: text-generation
base_model: aifeifei798/QiMing-Holos-Plus-Qwen3-8B
library_name: mlx
---
# QiMing-Holos-Plus-Qwen3-8B-q6-hi-mlx
This model [QiMing-Holos-Plus-Qwen3-8B-q6-hi-mlx](https://huggingface.co/QiMing-Holos-Plus-Qwen3-8B-q6-hi-mlx) was
converted to MLX format from [aifeifei798/QiMing-Holos-Plus-Qwen3-8B](https://huggingface.co/aifeifei798/QiMing-Holos-Plus-Qwen3-8B)
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("QiMing-Holos-Plus-Qwen3-8B-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)
```
|
tonberta42/blockassist-bc-moist_scurrying_mallard_1756082705
|
tonberta42
| 2025-08-25T00:45:45Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"moist scurrying mallard",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:45:27Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- moist scurrying mallard
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1756082606
|
Dejiat
| 2025-08-25T00:43:52Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:43:50Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
niotyere/blockassist-bc-pawing_bold_cat_1756082473
|
niotyere
| 2025-08-25T00:41:25Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"pawing bold cat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:41:13Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- pawing bold cat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1756082462
|
Dejiat
| 2025-08-25T00:41:25Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:41:23Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# 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_1756082328
|
kapalbalap
| 2025-08-25T00:39:31Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:39:26Z |
---
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).
|
coelacanthxyz/blockassist-bc-finicky_thriving_grouse_1756080599
|
coelacanthxyz
| 2025-08-25T00:37:20Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"finicky thriving grouse",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:37:13Z |
---
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).
|
NEETU852/blockassist-bc-stealthy_gliding_caribou_1756079551
|
NEETU852
| 2025-08-25T00:37:01Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stealthy gliding caribou",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:36:57Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- stealthy gliding caribou
---
# 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_1756082159
|
kapalbalap
| 2025-08-25T00:36:56Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:36:50Z |
---
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).
|
Dejiat/blockassist-bc-savage_unseen_bobcat_1756081818
|
Dejiat
| 2025-08-25T00:30:42Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"savage unseen bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:30:40Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- savage unseen bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
AnerYubo/blockassist-bc-shaggy_melodic_cobra_1756081775
|
AnerYubo
| 2025-08-25T00:29:38Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"shaggy melodic cobra",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:29:36Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- shaggy melodic cobra
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
AnerYubo/blockassist-bc-hairy_crested_fox_1756081771
|
AnerYubo
| 2025-08-25T00:29:34Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"hairy crested fox",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:29:31Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- hairy crested fox
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
roeker/blockassist-bc-quick_wiry_owl_1756081637
|
roeker
| 2025-08-25T00:29:01Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"quick wiry owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:28:03Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- quick wiry 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_1756081621
|
kapalbalap
| 2025-08-25T00:28:04Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:27:50Z |
---
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).
|
motza0025/blockassist-bc-sturdy_leaping_jaguar_1756079911
|
motza0025
| 2025-08-25T00:24:36Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"sturdy leaping jaguar",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:24:21Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- sturdy leaping jaguar
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
Adeoniye/blockassist-bc-voracious_barky_pheasant_1756081254
|
Adeoniye
| 2025-08-25T00:21:56Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"voracious barky pheasant",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:21:52Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- voracious barky pheasant
---
# 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_1756079730
|
koloni
| 2025-08-25T00:21:34Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"deadly graceful stingray",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:21:31Z |
---
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).
|
helmutsukocok/blockassist-bc-loud_scavenging_kangaroo_1756079495
|
helmutsukocok
| 2025-08-25T00:16:19Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"loud scavenging kangaroo",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:16:15Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- loud scavenging kangaroo
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
franklhusk/blockassist-bc-wild_alert_armadillo_1756080795
|
franklhusk
| 2025-08-25T00:14:03Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"wild alert armadillo",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:13:35Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- wild alert armadillo
---
# 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_1756080683
|
kapalbalap
| 2025-08-25T00:12:02Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:11:56Z |
---
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).
|
lilTAT/blockassist-bc-gentle_rugged_hare_1756080393
|
lilTAT
| 2025-08-25T00:07:16Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"gentle rugged hare",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:07:06Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- gentle rugged hare
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
roeker/blockassist-bc-quick_wiry_owl_1756080266
|
roeker
| 2025-08-25T00:05:54Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"quick wiry owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:05:14Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- quick wiry owl
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
vendi11/blockassist-bc-placid_placid_llama_1756080230
|
vendi11
| 2025-08-25T00:04:40Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"placid placid llama",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:04:37Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- placid placid llama
---
# 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_1756080179
|
kapalbalap
| 2025-08-25T00:03:58Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:03:52Z |
---
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).
|
russellyq/Qwen2.5-VL-3B-Instruct-SFT-2e
|
russellyq
| 2025-08-25T00:03:46Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"qwen2_5_vl",
"image-to-text",
"llama-factory",
"full",
"generated_from_trainer",
"base_model:Qwen/Qwen2.5-VL-3B-Instruct",
"base_model:finetune:Qwen/Qwen2.5-VL-3B-Instruct",
"license:other",
"text-generation-inference",
"endpoints_compatible",
"region:us"
] |
image-to-text
| 2025-08-24T23:59:07Z |
---
library_name: transformers
license: other
base_model: Qwen/Qwen2.5-VL-3B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: qwen2_5vl-3b-2e
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. -->
# qwen2_5vl-3b-2e
This model is a fine-tuned version of [/research/d7/gds/qyan24/model_weights/Qwen2.5-VL-3B-Instruct](https://huggingface.co//research/d7/gds/qyan24/model_weights/Qwen2.5-VL-3B-Instruct) on the Med-R1-SFT dataset.
## 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: 1
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use 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_ratio: 0.15
- num_epochs: 2.0
### Training results
### Framework versions
- Transformers 4.55.0
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.1
|
hertokredas55/blockassist-bc-barky_scurrying_jay_1756080158
|
hertokredas55
| 2025-08-25T00:03:18Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"barky scurrying jay",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-25T00:02:56Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- barky scurrying jay
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
hertokredas55/blockassist-bc-barky_scurrying_jay_1756079960
|
hertokredas55
| 2025-08-25T00:00:02Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"barky scurrying jay",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:59:38Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- barky scurrying jay
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
lordvader2009/medgemma-4b-it-lora64-aggregate-x1
|
lordvader2009
| 2025-08-24T23:58:14Z | 0 | 0 |
transformers
|
[
"transformers",
"tensorboard",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:google/medgemma-4b-it",
"base_model:finetune:google/medgemma-4b-it",
"endpoints_compatible",
"region:us"
] | null | 2025-08-24T22:24:37Z |
---
base_model: google/medgemma-4b-it
library_name: transformers
model_name: medgemma-4b-it-lora64-aggregate-x1
tags:
- generated_from_trainer
- sft
- trl
licence: license
---
# Model Card for medgemma-4b-it-lora64-aggregate-x1
This model is a fine-tuned version of [google/medgemma-4b-it](https://huggingface.co/google/medgemma-4b-it).
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="lordvader2009/medgemma-4b-it-lora64-aggregate-x1", 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 SFT.
### Framework versions
- TRL: 0.21.0
- Transformers: 4.55.4
- Pytorch: 2.8.0+cu126
- 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}}
}
```
|
chainway9/blockassist-bc-untamed_quick_eel_1756078359
|
chainway9
| 2025-08-24T23:58:06Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"untamed quick eel",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:58:03Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- untamed quick eel
---
# 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_1756079785
|
ggozzy
| 2025-08-24T23:57:39Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stubby yapping mandrill",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:57:33Z |
---
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).
|
alpcaferoglu/Qwen2.5-Coder-3B-Instruct_bd_cs_t2s_r32_a32_e4_bs4_gas8_lr2e-05_fs6f_cvdt_sftreason
|
alpcaferoglu
| 2025-08-24T23:57:08Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"unsloth",
"arxiv:1910.09700",
"endpoints_compatible",
"region:us"
] | null | 2025-08-24T05:14:41Z |
---
library_name: transformers
tags:
- unsloth
---
# 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]
|
nema122/blockassist-bc-robust_fluffy_ram_1756079404
|
nema122
| 2025-08-24T23:51:19Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"robust fluffy ram",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:51:17Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- robust fluffy ram
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
lilTAT/blockassist-bc-gentle_rugged_hare_1756079377
|
lilTAT
| 2025-08-24T23:50:22Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"gentle rugged hare",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:50:12Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- gentle rugged hare
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
1sf/deepseek_r1_0528_sft_bird_sql
|
1sf
| 2025-08-24T23:50:06Z | 0 | 0 |
transformers
|
[
"transformers",
"safetensors",
"generated_from_trainer",
"sft",
"trl",
"base_model:deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
"base_model:finetune:deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
"endpoints_compatible",
"region:us"
] | null | 2025-08-24T20:58:11Z |
---
base_model: deepseek-ai/DeepSeek-R1-0528-Qwen3-8B
library_name: transformers
model_name: deepseek_r1_0528_sft_bird_sql
tags:
- generated_from_trainer
- sft
- trl
licence: license
---
# Model Card for deepseek_r1_0528_sft_bird_sql
This model is a fine-tuned version of [deepseek-ai/DeepSeek-R1-0528-Qwen3-8B](https://huggingface.co/deepseek-ai/DeepSeek-R1-0528-Qwen3-8B).
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="1sf/deepseek_r1_0528_sft_bird_sql", 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 SFT.
### Framework versions
- TRL: 0.21.0
- Transformers: 4.55.4
- Pytorch: 2.8.0
- Datasets: 3.2.0
- 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}}
}
```
|
toupyoui/blockassist-bc-pensive_sniffing_sloth_1756079293
|
toupyoui
| 2025-08-24T23:48:26Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"pensive sniffing sloth",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:48:14Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- pensive sniffing sloth
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
jammerbop/blockassist-bc-pudgy_nimble_bobcat_1756079276
|
jammerbop
| 2025-08-24T23:48:08Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"pudgy nimble bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:47:56Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- pudgy nimble bobcat
---
# 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_1756077782
|
koloni
| 2025-08-24T23:47:48Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"deadly graceful stingray",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:47:45Z |
---
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).
|
duppbuy/blockassist-bc-iridescent_aquatic_parrot_1756079252
|
duppbuy
| 2025-08-24T23:47:47Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"iridescent aquatic parrot",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:47:33Z |
---
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).
|
tremtostar/blockassist-bc-stinging_giant_bat_1756079145
|
tremtostar
| 2025-08-24T23:46:27Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stinging giant bat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:46:04Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- stinging giant bat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
eternaaall/blockassist-bc-running_finicky_flamingo_1756077325
|
eternaaall
| 2025-08-24T23:46:22Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"running finicky flamingo",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:46:14Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- running finicky flamingo
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
tremtostar/blockassist-bc-stinging_giant_bat_1756078968
|
tremtostar
| 2025-08-24T23:43:29Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stinging giant bat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:43:06Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- stinging giant bat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
hridyakachi/blockassist-bc-wily_burrowing_swan_1756078388
|
hridyakachi
| 2025-08-24T23:34:14Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"wily burrowing swan",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:34:10Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- wily burrowing swan
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
IvanJAjebu/blockassist-bc-thorny_slender_capybara_1756078364
|
IvanJAjebu
| 2025-08-24T23:33:59Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"thorny slender capybara",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:33:46Z |
---
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).
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756078383
|
kapalbalap
| 2025-08-24T23:33:47Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:33:41Z |
---
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).
|
calegpedia/blockassist-bc-stealthy_slimy_rooster_1756076578
|
calegpedia
| 2025-08-24T23:27:43Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stealthy slimy rooster",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:27:40Z |
---
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).
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756077902
|
kapalbalap
| 2025-08-24T23:25:46Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:25:40Z |
---
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_1756077872
|
ggozzy
| 2025-08-24T23:25:46Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"stubby yapping mandrill",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:25:40Z |
---
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).
|
cloud1991/blockassist-bc-bold_skilled_bobcat_1756077867
|
cloud1991
| 2025-08-24T23:25:17Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"bold skilled bobcat",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:25:10Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- bold skilled bobcat
---
# Gensyn BlockAssist
Gensyn's BlockAssist is a distributed extension of the paper [AssistanceZero: Scalably Solving Assistance Games](https://arxiv.org/abs/2504.07091).
|
toupyoui/blockassist-bc-secretive_unseen_python_1756077880
|
toupyoui
| 2025-08-24T23:25:03Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"secretive unseen python",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:24:43Z |
---
tags:
- gensyn
- blockassist
- gensyn-blockassist
- minecraft
- secretive unseen python
---
# 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_1756077580
|
kapalbalap
| 2025-08-24T23:20:26Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:20:13Z |
---
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).
|
sampingkaca72/blockassist-bc-armored_stealthy_elephant_1756075937
|
sampingkaca72
| 2025-08-24T23:19:57Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"armored stealthy elephant",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:19:54Z |
---
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).
|
kapalbalap/blockassist-bc-peaceful_wary_owl_1756077424
|
kapalbalap
| 2025-08-24T23:17:47Z | 0 | 0 | null |
[
"gensyn",
"blockassist",
"gensyn-blockassist",
"minecraft",
"peaceful wary owl",
"arxiv:2504.07091",
"region:us"
] | null | 2025-08-24T23:17:42Z |
---
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).
|
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