huggingface-projects (Huggingface Projects)

lunarflu

posted an update about 9 hours ago

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The #1 trending AI/ML dataset today 🏆

Massive scale, diversity and end-to-end potential from nvidia !
nvidia/PhysicalAI-Autonomous-Vehicles

lunarflu

posted an update about 9 hours ago

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63

The new King 👑has arrived!

Moonshot AI now the top model on Hugging Face 🔥
moonshotai/Kimi-K2-Thinking

lunarflu

posted an update about 9 hours ago

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279

💸🤑You don’t need 100 GPUs to train something amazing!

Our Smol Training Playbook teaches you a better path to world-class LLMs, for free!

Check out the #1 trending space on 🤗 :
HuggingFaceTB/smol-training-playbook

sergiopaniego

updated a dataset about 10 hours ago

huggingface-projects/Deep-RL-Course-Certification

Viewer • Updated about 10 hours ago • 1.6k • 233 • 16

pcuenq

updated a dataset 1 day ago

huggingface-projects/drlc-leaderboard-data

Viewer • Updated 1 day ago • 46.8k • 3.18k • 2

AdinaY

posted an update 2 days ago

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Kimi K2 Thinking is now live on the hub 🔥

moonshotai/Kimi-K2-Thinking

✨ 1T MoE for deep reasoning & tool use
✨ Native INT4 quantization = 2× faster inference
✨ 256K context window
✨ Modified MIT license

AdinaY

posted an update 3 days ago

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259

Chinese open source AI in October wasn’t about bigger models, it was about real world impact 🔥

https://huggingface.co/collections/zh-ai-community/october-2025-china-open-source-highlights

✨ Vision-Language & OCR wave 🌊
- DeepSeek-OCR : 3B
- PaddleOCR-VL : 0.9B
- Qwen3-VL : 2B / 4B / 8B / 32B /30B-A3B
- Open-Bee: Bee-8B-RL
- http://Z.ai Glyph :10B

OCR is industrializing, the real game now is understanding the (long context) document, not just reading it.

✨ Text generation: scale or innovation?
- MiniMax-M2: 229B
- Antgroup Ling-1T & Ring-1T
- Moonshot Kimi-Linear : linear-attention challenger
- Kwaipilot KAT-Dev

Efficiency is the key.

✨ Any-to-Any & World-Model : one step forward to the real world
- BAAI Emu 3.5
- Antgroup Ming-flash-omni
- HunyuanWorld-Mirror: 3D

Aligning with the “world model” globally

✨ Audio & Speech + Video & Visual: released from entertainment labs to delivery platforms
- SoulX-Podcast TTS
- LongCat-Audio-Codec & LongCat-Video by Meituan delivery paltform
- xiabs DreamOmni 2

Looking forward to what's next 🚀

AdinaY

authored a paper 3 days ago

RoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies

Paper • 2510.17950 • Published 19 days ago • 4

sergiopaniego

posted an update 4 days ago

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5073

fine-tuning a 14B model with TRL + SFT on a free Colab (T4 GPU)?
thanks to the latest TRL optimizations, you actually can!
sharing a new notebook showing how to do it 😎

colab: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/sft_trl_lora_qlora.ipynb

notebooks in TRL: https://github.com/huggingface/trl/tree/main/examples/notebooks

2 replies

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sergiopaniego

posted an update 6 days ago

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Gave a smol 🤏 intro to Agents using smolagents last Monday!
Sharing the slides in case you're curious. They serve as a gentle first step into the Agents Course we developed at @huggingface 🫶🫶

Course: https://huggingface.co/learn/agents-course/unit0/introduction

Workshop material: https://github.com/sergiopaniego/talks/tree/main/intro_to_agents

AdinaY

posted an update 8 days ago

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358

Kimi Linear🚀 Hybrid linear attention model from Moonshot AI

https://huggingface.co/collections/moonshotai/kimi-linear-a3b

✨ 48B total/ 3B active - MIT license
✨ Up to 1M context
✨ 84.3 on RULER (128k) with 3.98× speedup
✨ Hybrid KDA + MLA architecture for peak throughput & quality

sergiopaniego

posted an update 9 days ago

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Sharing the slides from yesterday's talk about "Fine Tuning with TRL" from the @TogetherAgent x @huggingface workshop we hosted in our Paris office 🎃!

Link: https://github.com/sergiopaniego/talks/blob/main/fine_tuning_with_trl/Fine%20tuning%20with%20TRL%20(Oct%2025).pdf

sergiopaniego

posted an update 10 days ago

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On-Policy distillation is trendy! and super useful!

HuggingFaceH4/on-policy-distillation

AdinaY

posted an update 12 days ago

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Ming-flash-omni Preview 🚀 Multimodal foundation model from AntGroup

inclusionAI/Ming-flash-omni-Preview

✨ Built on Ling-Flash-2.0: 10B total/6B active
✨ Generative segmentation-as-editing
✨ SOTA contextual & dialect ASR
✨ High-fidelity image generation

AdinaY

posted an update 12 days ago

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Glyph 🔥 a framework that scales context length by compressing text into images and processing them with vision–language models, released by Z.ai.

Paper:https://huggingface.co/papers/2510.17800
Model:https://huggingface.co/zai-org/Glyph

✨ Compresses long sequences visually to bypass token limits
✨ Reduces computational and memory costs
✨ Preserves meaning through multimodal encoding
✨ Built on GLM-4.1V-9B-Base

sergiopaniego

posted an update 16 days ago

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Meet OpenEnv 👋, an open ecosystem of environments for intelligent agents. Build, share, and test agents safely and consistently.

Ideal for training with TRL (we include examples🤓), deployment, and community collaboration via the HF Hub

Blog: https://huggingface.co/blog/openenv
Hub for Environments:

openenv
OpenEnv repo: https://github.com/meta-pytorch/OpenEnv
Try it out using TRL: https://huggingface.co/docs/trl/main/en/openenv

1 reply

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AdinaY

posted an update 17 days ago

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HunyuanWorld Mirror🔥a versatile feed forward model for universal 3D world reconstruction by Tencent

tencent/HunyuanWorld-Mirror

✨ Any prior in → 3D world out
✨ Mix camera, intrinsics, depth as priors
✨ Predict point clouds, normals, Gaussians & more in one pass
✨ Unified architecture for all 3D task

andito

authored a paper 17 days ago

FineVision: Open Data Is All You Need

Paper • 2510.17269 • Published 20 days ago • 62

andito

posted an update 18 days ago

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Finally, our new paper is out! "𝗙𝗶𝗻𝗲𝗩𝗶𝘀𝗶𝗼𝗻: 𝗢𝗽𝗲𝗻 𝗗𝗮𝘁𝗮 𝗜𝘀 𝗔𝗹𝗹 𝗬𝗼𝘂 𝗡𝗲𝗲𝗱"! 🥳
FineVision: Open Data Is All You Need (2510.17269)

If you've ever trained a VLM, you know this problem: nobody shares their data mixtures. It's a black box, making replicating SOTA work impossible.
We wanted to change that.

FineVision unifies 200 sources into 24 million samples. With 17.3 million images and 9.5 billion answer tokens, it's the largest open resource of its kind.

In the paper, we share how we built it:
🔍 finding and cleaning data at scale
🧹 removing excessive duplicates across sources
🤗 decontaminating against 66 public benchmarks

My favorite part is Figure 6 (in the video!). It's our visual diversity analysis. It shows that FineVision isn't just bigger; it's more balanced and conceptually richer than other open datasets.
NVIDIA's Eagle 2 paper highlighted just how critical this visual diversity is, and our results confirm it: models trained on FineVision consistently outperform those trained on any other open dataset on 11 benchmarks!

🎉 To celebrate the paper, I’m also releasing a concatenated and shuffled version of the full dataset! 👉HuggingFaceM4/FineVision_full_shuffled

It’s ready to stream, so you can start training your own models right away:

from datasets import load_dataset
d = load_dataset("HuggingFaceM4/FineVision_full_shuffled", split="train", streaming=True)
print(next(iter(d)))

A big shoutout to the first authors: Luis Wiedmann and Orr Zohar. They are rockstars!

merve

posted an update 19 days ago

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deepseek-ai/DeepSeek-OCR is out! 🔥 my take ⤵️
> pretty insane it can parse and re-render charts in HTML
> it uses CLIP and SAM features concatenated, so better grounding
> very efficient per vision tokens/performance ratio
> covers 100 languages