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isaaccorley  updated a dataset 1 day ago
torchgeo/ucmerced
isaaccorley  updated a model 4 days ago
torchgeo/presto
isaaccorley  published a model 4 days ago
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prithivMLmods 
posted an update 1 day ago
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1235
Try Liquid AI's all-new multimodal models: LFM2-VL-1.6B & LFM2-VL-450M! Demo with the Gradio UI and ReportLab support and both models are runnable on T4 GPU!

↗ LFM2-VL-1.6B-LiquidAI : https://github.com/PRITHIVSAKTHIUR/Multimodal-Outpost-Notebooks/blob/main/LFM2-VL-1.6B-LiquidAI/LFM2-VL-1.6B_ReportLab.ipynb

↗ LFM2-VL-450M-LiquidAI : https://github.com/PRITHIVSAKTHIUR/Multimodal-Outpost-Notebooks/blob/main/LFM2-VL-450M-LiquidAI/LFM2-VL-450M_ReportLab.ipynb

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To know more about it, visit the multimodal outpost notebooks !!
  • 1 reply
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ZennyKenny 
posted an update 1 day ago
isaaccorley 
updated a dataset 1 day ago
isaaccorley 
updated a model 4 days ago
isaaccorley 
published a model 4 days ago
ajstewart 
updated a dataset 4 days ago
prithivMLmods 
posted an update 5 days ago
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4289
On the verge of releasing Poseidon-Reasoning-5M, a dataset built to excel in general thought processes, mathematics, and science across a diverse mixture of domains, I’m also dropping the Gargantua-R1-Compact dataset, a collection of over six million high-quality reasoning QA pair traces. 🤗🚀

✦ Gargantua-R1-Compact : prithivMLmods/Gargantua-R1-Compact

from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Gargantua-R1-Compact", split="train")

Additionally, I’m adding the mini version of Gargantua — the Gargantua-R1-Wee : prithivMLmods/Gargantua-R1-Wee

from datasets import load_dataset

dataset = load_dataset("prithivMLmods/Gargantua-R1-Wee", split="train")

The composition spans 73.93% core mathematical reasoning involving problems, proofs, and computational challenges, 12.11% across diverse scientific domains such as physics, chemistry, biology, and interdisciplinary topics, 11.35% in competitive coding covering algorithms and data structures, 1.37% in academic science focusing on research-level methodology, 0.95% in creative and analytical reasoning through logic puzzles and problem-solving tasks, 0.25% in specialized technical areas like MLOps, LLMs, diffusion models, and CUDA, and 0.06% involving data from graphs and charts converted into structured JSON formats. Designed with both rich contextual depth and formal structural clarity, Gargantua-R1-Compact is an optimal resource for advancing research in symbolic reasoning, interpretability, and high-precision question answering in mathematical domains.

✦ Collection : prithivMLmods/gargantua-r1-mod-6896bfd7834e82b89ad2b38b


To know more about it, visit the dataset card of the respective dataset. !!
prithivMLmods 
posted an update 6 days ago
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2147
I've added the demo of the openbmb/MiniCPM-V-4 model to the Hugging Face Space:
prithivMLmods/Multimodal-VLM-Thinking

✨ MiniCPM-V 4.0 is the latest efficient model in the MiniCPM-V series. The model is built based on SigLIP2-400M and MiniCPM4-3B, with a total of 4.1B parameters. It inherits the strong single-image, multi-image, and video understanding performance of MiniCPM-V 2.6 with largely improved efficiency.

✨ With only 4.1B parameters, MiniCPM-V 4.0 achieves an average score of 69.0 on OpenCompass, a comprehensive evaluation of 8 popular benchmarks. This performance surpasses GPT-4.1-mini-20250414, MiniCPM-V 2.6 (8.1B parameters, OpenCompass 65.2), and Qwen2.5-VL-3B-Instruct (3.8B parameters, OpenCompass 64.5). It also shows good performance in multi-image and video understanding.

The community GPU grant was given by Hugging Face — special thanks to them. 🤗🚀

To know more about it, visit the model card of the respective model. !!
prithivMLmods 
posted an update 9 days ago
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4171
Qwen Image – The Latest Image Generation Model🔥

Below are some samples generated using the Qwen Image Diffusion Model. Qwen-Image, a 20B MMDiT model for next-generation text-to-image generation, preserves typographic details, layout coherence, and contextual harmony with stunning accuracy. It is especially strong at creating stunning graphic posters with native text. The model is now open-source. [ 𝚀𝚠𝚎𝚗-𝙸𝚖𝚊𝚐𝚎 : Qwen/Qwen-Image ]

⤷ Try the Qwen Image demo here: prithivMLmods/Qwen-Image-Diffusion

⤷ Qwen-Image Technical Report : Qwen-Image Technical Report (2508.02324)
⤷ Qwen Image [GitHub] : https://github.com/QwenLM/Qwen-Image

Even more impressively, it demonstrates a strong ability to understand images. The model supports a wide range of vision-related tasks such as object detection, semantic segmentation, depth and edge (Canny) estimation, novel view synthesis, and image super-resolution. While each task is technically distinct, they can all be viewed as advanced forms of intelligent image editing driven by deep visual understanding. Collectively, these capabilities position Qwen-Image as more than just a tool for generating appealing visuals, it serves as a versatile foundation model for intelligent visual creation and transformation, seamlessly blending language, layout, and imagery.

Qwen-Image uses a dual-stream MMDiT architecture with a frozen Qwen2.5-VL, VAE encoder, RMSNorm for QK-Norm, LayerNorm elsewhere, and a custom MSRoPE scheme for joint image-text positional encoding.

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To know more about it, visit the model card of the respective model. !!
prithivMLmods 
posted an update 12 days ago
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3146
Introducing Camel-Doc-OCR-080125(v2), a document content-structure retrieval VLM designed for content extraction and summarization. This is the second model in the Camel Doc OCR VLM series, following Camel-Doc-OCR-062825(v1). The new version fixes formal table reconstruction issues in both en and zh language, achieving optimal performance for long-context inferences.🤗🐪

⤷ Camel-Doc-OCR(v2) : prithivMLmods/Camel-Doc-OCR-080125
⤷ Camel-Doc-OCR(v1) : prithivMLmods/Camel-Doc-OCR-062825
⤷ Demo : prithivMLmods/core-OCR

Multimodal Model Collections and Spaces:

➝ Camel-Doc-OCR : prithivMLmods/camel-doc-ocr-080125-688c0c61c5dba648756f31f8
➝ Vision-Language (VLr) : prithivMLmods/vision-language-for-reasoning-vlr-6889b3f45917352b5e3a6f7a
➝ Multimodal Spaces : prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0
➝ Multimodal VLMs : prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027

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To know more about it, visit the model card of the respective model. !!
  • 2 replies
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isaaccorley 
updated 2 models 12 days ago
isaaccorley 
updated 2 models 13 days ago
isaaccorley 
published 4 models 13 days ago
isaaccorley 
updated a model 14 days ago
prithivMLmods 
posted an update 14 days ago
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1071
Exciting to bring the explicitly grounded experimental reasoning model, Lumian-VLR-7B-Thinking, built on top of Qwen2.5-VL, featuring reasoning-aware trajectories with enhanced spatial perception. Along with this, we’ve also added a demo for the model while bringing some of the latest and most interesting models available on the hub to make full use of the remaining resources.

✨ Multimodal-VLM-Thinking : prithivMLmods/Multimodal-VLM-Thinking
✨ Multimodal-VLM-OCR : prithivMLmods/Multimodal-VLM-OCR

✦ Models used in these spaces:

✨ Lumian-VLR-7B-Thinking : prithivMLmods/Lumian-VLR-7B-Thinking
✨ Enesidaon-VLR-7B-no-Thinking : prithivMLmods/Enesidaon-VLR-7B-no-Thinking
✨ GLM-4.1V-9B-Thinking : zai-org/GLM-4.1V-9B-Thinking
✨ DREX-062225-exp : prithivMLmods/DREX-062225-exp & more ...

✦ Multimodal Model Collections and Spaces:

✨ Vision-Language (VLr) : prithivMLmods/vision-language-for-reasoning-vlr-6889b3f45917352b5e3a6f7a
✨ Multimodal Spaces : prithivMLmods/multimodal-implementations-67c9982ea04b39f0608badb0
✨ Multimodal VLMs : prithivMLmods/multimodal-vlms-until-july25-688312e6b840e1e156f13027

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To know more about it, visit the model card of the respective model. !!