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victor
updated
a
Space
3 minutes ago
sergiopaniego
updated
a
dataset
about 17 hours ago
Post
383
Chinese open source AI in December 2025 was about the stack coming together: open, end to end, and ready to ship 🔥
https://huggingface.co/collections/zh-ai-community/december-2025-china-open-source-highlights
✨ Big wave of foundation models: still scaling, but efficiency, reasoning, and deployment now matter more than size
- DeepSeek-V3.2
- Z.ai GLM-4.7
- MiniMax-M2.1
- Xiaomi: MiMo-V2-Flash
✨ Multimodal reasoning is now default
- Z.ai GLM-4.6V
- Z.ai AutoGLM-Phone 9B
- Bytedance: Dolphin-v2
✨ Image & video: editable assets and real workflows
- Qwen-Image-Layered / Image-2512
- Meituan: LongCat-Image & Image Edit
- AIDC: Ovis-Image-7B
- Live-Avatar / LongCat-Video-Avatar
- HY-WorldPlay / RealVideo
✨ Audio goes edge ready
- GLM-ASR-Nano / Fun-ASR-Nano
- GLM-TTS / VoxCPM1.5
- CosyVoice 0.5B
✨ The quiet backbone: data & infrastructure
- Finch (FinWorkBench)
- Tencent ARC: TimeLens-100K
- BIGAI: TongSIM-Asset
- MiniMax: VTP-Base
✨ Also congrats on Minimax and Z.ai announced their IPOs and Moonshot announced a new $500M funding round 🔥
Like everyone else, I was OOO at the end of December, so feel free to share (in comments or PR) any I missed in this list!
https://huggingface.co/collections/zh-ai-community/december-2025-china-open-source-highlights
✨ Big wave of foundation models: still scaling, but efficiency, reasoning, and deployment now matter more than size
- DeepSeek-V3.2
- Z.ai GLM-4.7
- MiniMax-M2.1
- Xiaomi: MiMo-V2-Flash
✨ Multimodal reasoning is now default
- Z.ai GLM-4.6V
- Z.ai AutoGLM-Phone 9B
- Bytedance: Dolphin-v2
✨ Image & video: editable assets and real workflows
- Qwen-Image-Layered / Image-2512
- Meituan: LongCat-Image & Image Edit
- AIDC: Ovis-Image-7B
- Live-Avatar / LongCat-Video-Avatar
- HY-WorldPlay / RealVideo
✨ Audio goes edge ready
- GLM-ASR-Nano / Fun-ASR-Nano
- GLM-TTS / VoxCPM1.5
- CosyVoice 0.5B
✨ The quiet backbone: data & infrastructure
- Finch (FinWorkBench)
- Tencent ARC: TimeLens-100K
- BIGAI: TongSIM-Asset
- MiniMax: VTP-Base
✨ Also congrats on Minimax and Z.ai announced their IPOs and Moonshot announced a new $500M funding round 🔥
Like everyone else, I was OOO at the end of December, so feel free to share (in comments or PR) any I missed in this list!
Post
1250
👉 What happened in AI in 2025? 👈
We prepared the 2025 version of the HF AI Timeline Grid, highlighting open vs API-based model releases, and allowing you to browse and filter by access, modality, and release type!
Play with it here:
2025-ai-timeline/2025-ai-timeline
Here's my personal quarterly TL;DR:
1️⃣ Q1 — Learning to Reason
Deepseek not only releases a top-notch reasoning model, but shows how to train them and compete with closed frontier models. OpenAI debuts Deep Research.
Significant milestones: DeepSeek R1 & R1-Zero, Qwen 2.5 VL, OpenAI Deep Research, Gemini 2.5 Pro (experimental)
2️⃣ Q2 — Multimodality and Coding
More LLMs embrace multimodality by default, and there's a surge in coding agents. Strong vision, audio, and generative models emerge.
Significant milestones: Llama 4, Qwen 3, Imagen 4, OpenAI Codex, Google Jules, Claude 4
3️⃣ Q3 — "Gold" rush, OpenAI opens up, the community goes bananas
Flagship models get gold in Math olympiads and hard benchmarks. OpenAI releases strong open source models and Google releases the much anticipated nano-banana for image generation and editing. Agentic workflows become commonplace.
Significant milestones: Gemini and OpenAI IMO Gold, gpt-oss, Gemini 2.5 Flash Image, Grok 4, Claude Sonnet 4.5
4️⃣ Q4 — Mistral returns, leaderboard hill-climbing
Mistral is back with updated model families. All labs release impressive models to wrap up the year!
Significant milestones: Claude Opus 4.5, DeepSeek Math V2, FLUX 2, GPT 5.1, Kimi K2 Thinking, Nano Banana Pro, GLM 4.7, Gemini 3, Mistral 3, MiniMax M2.1 🤯
Credits
🙏 NHLOCAL for the source data https://github.com/NHLOCAL/AiTimeline
🫡 @reach-vb for the original idea, design and recipe
🙌 @ariG23498 and yours truly for compiling and verifying the 2025 edition
🥳 Here's to 2026, wishing it becomes the best year ever for open releases and on-device-first use-cases! 🥂
We prepared the 2025 version of the HF AI Timeline Grid, highlighting open vs API-based model releases, and allowing you to browse and filter by access, modality, and release type!
Play with it here:
2025-ai-timeline/2025-ai-timeline
Here's my personal quarterly TL;DR:
1️⃣ Q1 — Learning to Reason
Deepseek not only releases a top-notch reasoning model, but shows how to train them and compete with closed frontier models. OpenAI debuts Deep Research.
Significant milestones: DeepSeek R1 & R1-Zero, Qwen 2.5 VL, OpenAI Deep Research, Gemini 2.5 Pro (experimental)
2️⃣ Q2 — Multimodality and Coding
More LLMs embrace multimodality by default, and there's a surge in coding agents. Strong vision, audio, and generative models emerge.
Significant milestones: Llama 4, Qwen 3, Imagen 4, OpenAI Codex, Google Jules, Claude 4
3️⃣ Q3 — "Gold" rush, OpenAI opens up, the community goes bananas
Flagship models get gold in Math olympiads and hard benchmarks. OpenAI releases strong open source models and Google releases the much anticipated nano-banana for image generation and editing. Agentic workflows become commonplace.
Significant milestones: Gemini and OpenAI IMO Gold, gpt-oss, Gemini 2.5 Flash Image, Grok 4, Claude Sonnet 4.5
4️⃣ Q4 — Mistral returns, leaderboard hill-climbing
Mistral is back with updated model families. All labs release impressive models to wrap up the year!
Significant milestones: Claude Opus 4.5, DeepSeek Math V2, FLUX 2, GPT 5.1, Kimi K2 Thinking, Nano Banana Pro, GLM 4.7, Gemini 3, Mistral 3, MiniMax M2.1 🤯
Credits
🙏 NHLOCAL for the source data https://github.com/NHLOCAL/AiTimeline
🫡 @reach-vb for the original idea, design and recipe
🙌 @ariG23498 and yours truly for compiling and verifying the 2025 edition
🥳 Here's to 2026, wishing it becomes the best year ever for open releases and on-device-first use-cases! 🥂
Post
1075
MiniMax M2.1 blog is out🔥
https://huggingface.co/blog/MiniMaxAI/multilingual-and-multi-task-coding-with-strong-gen
Only a year into open source, MiniMax is already making a great impact. Not only through solid models/products, but also by how well the team uses community platforms like Hugging Face.
HF Teams, blogs, Daily Papers, Spaces as project pages, and always experimenting with new ways to engage. Super impressive!
https://huggingface.co/blog/MiniMaxAI/multilingual-and-multi-task-coding-with-strong-gen
Only a year into open source, MiniMax is already making a great impact. Not only through solid models/products, but also by how well the team uses community platforms like Hugging Face.
HF Teams, blogs, Daily Papers, Spaces as project pages, and always experimenting with new ways to engage. Super impressive!
Post
3093
2025.1 - DeepSeek entered the scene, backed by High Flyer Quant
2026.1 - IQuest enters the game, backed by Uniquant Quant 📈 and launching IQuest-Coder on huggingface
https://huggingface.co/collections/IQuestLab/iquest-coder
✨ 40B models: Instruct / Thinking / Loop
✨ Loop = MoE-level performance with only ~5% extra training cost
✨ Native 128K context
2026.1 - IQuest enters the game, backed by Uniquant Quant 📈 and launching IQuest-Coder on huggingface
https://huggingface.co/collections/IQuestLab/iquest-coder
✨ 40B models: Instruct / Thinking / Loop
✨ Loop = MoE-level performance with only ~5% extra training cost
✨ Native 128K context
- 1 reply
sergiopaniego
posted
an
update
4 days ago
Post
2379
The list of hands-on notebooks (some beginner-friendly!) to get started with fine-tuning using TRL keeps growing!!
• SFT
• GRPO
• Tool calling & agents
• RL environments with OpenEnv
• LLMs and VLMs
✨ Many run on FREE Colab, making it super easy to get started fast!
https://github.com/huggingface/trl/tree/main/examples/notebooks
• SFT
• GRPO
• Tool calling & agents
• RL environments with OpenEnv
• LLMs and VLMs
✨ Many run on FREE Colab, making it super easy to get started fast!
https://github.com/huggingface/trl/tree/main/examples/notebooks
akhaliq
submitted
2
papers
to Daily Papers
4 days ago
AdinaY
submitted
a
paper
to Daily Papers
5 days ago
sergiopaniego
posted
an
update
7 days ago
Post
335
As the year comes to an end, it’s a good moment to catch up on some of the best long-form pieces published by the
@huggingface
team.
I’ve gathered them all here if you want to read or save them for later:
https://huggingface.co/collections/sergiopaniego/research-and-long-form-blog-posts
I’ve gathered them all here if you want to read or save them for later:
https://huggingface.co/collections/sergiopaniego/research-and-long-form-blog-posts
sergiopaniego
posted
an
update
8 days ago
Post
2181
This super detailed tutorial by
@Paulescu
is pure gold 🪙 "Fine-tuning a Small Language Model for browser control with GRPO and OpenEnv"
LFM2-350M ( @LiquidAI ) + BrowserGym (OpenEnv) + GRPO (TRL) for learning browser control 🤝
https://paulabartabajo.substack.com/p/fine-tuning-lfm2-350m-for-browser
LFM2-350M ( @LiquidAI ) + BrowserGym (OpenEnv) + GRPO (TRL) for learning browser control 🤝
https://paulabartabajo.substack.com/p/fine-tuning-lfm2-350m-for-browser
sergiopaniego
posted
an
update
14 days ago
Post
412
if you’re on holidays 🎄 and want some reading, here are blogs I contributed to this year:
🦄 VLMs in TRL: https://huggingface.co/blog/trl-vlm-alignment
🦖 VLMs in 2025: https://huggingface.co/blog/vlms-2025
👾 tokenization in transformers v5: https://huggingface.co/blog/tokenizers
🛸 faster transformers: https://huggingface.co/blog/faster-transformers
🦄 VLMs in TRL: https://huggingface.co/blog/trl-vlm-alignment
🦖 VLMs in 2025: https://huggingface.co/blog/vlms-2025
👾 tokenization in transformers v5: https://huggingface.co/blog/tokenizers
🛸 faster transformers: https://huggingface.co/blog/faster-transformers
sergiopaniego
posted
an
update
15 days ago
Post
1934
The Christmas holidays are here! 🎄
Thinking about learning something new in AI?
@huggingface offers 12 FREE courses covering all the relevant topics, for every level of experience. A great challenge for the holidays (and worth saving for later 🙄)
Let’s explore them!
🧠 𝗟𝗟𝗠 𝗖𝗼𝘂𝗿𝘀𝗲: large language models with HF tools
https://huggingface.co/learn/llm-course
🤖 𝗔𝗴𝗲𝗻𝘁𝘀 𝗖𝗼𝘂𝗿𝘀𝗲: build and deploy AI agents
https://huggingface.co/learn/agents-course
🎨 𝗗𝗶𝗳𝗳𝘂𝘀𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲: diffusion models with 🤗 Diffusers
https://huggingface.co/learn/diffusion-course
🔊 𝗔𝘂𝗱𝗶𝗼 𝗖𝗼𝘂𝗿𝘀𝗲: transformers for audio tasks
https://huggingface.co/learn/audio-course
🎮 𝗗𝗲𝗲𝗽 𝗥𝗟 𝗖𝗼𝘂𝗿𝘀𝗲: deep reinforcement learning
https://huggingface.co/learn/deep-rl-course
👁️ 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲: modern computer vision with HF
https://huggingface.co/learn/computer-vision-course
🦾 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗖𝗼𝘂𝗿𝘀𝗲 (𝗟𝗲𝗥𝗼𝗯𝗼𝘁): learning-based robotics
https://huggingface.co/learn/robotics-course
🧩 𝗠𝗖𝗣 𝗖𝗼𝘂𝗿𝘀𝗲: Model Context Protocol explained
https://huggingface.co/learn/mcp-course
🧪 𝗔 𝗦𝗺𝗼𝗹 𝗖𝗼𝘂𝗿𝘀𝗲: post-training AI models
https://huggingface.co/learn/a-smol-course
🕹️ 𝗠𝗟 𝗳𝗼𝗿 𝗚𝗮𝗺𝗲𝘀: AI in game development
https://huggingface.co/learn/ml-for-games-course
🧊 𝗠𝗟 𝗳𝗼𝗿 𝟯𝗗: machine learning for 3D data
https://huggingface.co/learn/ml-for-3d-course
📘 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗔𝗜 𝗖𝗼𝗼𝗸𝗯𝗼𝗼𝗸: practical AI notebooks
https://huggingface.co/learn/cookbook
All of them can be found here: https://huggingface.co/learn
Thinking about learning something new in AI?
@huggingface offers 12 FREE courses covering all the relevant topics, for every level of experience. A great challenge for the holidays (and worth saving for later 🙄)
Let’s explore them!
🧠 𝗟𝗟𝗠 𝗖𝗼𝘂𝗿𝘀𝗲: large language models with HF tools
https://huggingface.co/learn/llm-course
🤖 𝗔𝗴𝗲𝗻𝘁𝘀 𝗖𝗼𝘂𝗿𝘀𝗲: build and deploy AI agents
https://huggingface.co/learn/agents-course
🎨 𝗗𝗶𝗳𝗳𝘂𝘀𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲: diffusion models with 🤗 Diffusers
https://huggingface.co/learn/diffusion-course
🔊 𝗔𝘂𝗱𝗶𝗼 𝗖𝗼𝘂𝗿𝘀𝗲: transformers for audio tasks
https://huggingface.co/learn/audio-course
🎮 𝗗𝗲𝗲𝗽 𝗥𝗟 𝗖𝗼𝘂𝗿𝘀𝗲: deep reinforcement learning
https://huggingface.co/learn/deep-rl-course
👁️ 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆 𝗖𝗼𝗺𝗽𝘂𝘁𝗲𝗿 𝗩𝗶𝘀𝗶𝗼𝗻 𝗖𝗼𝘂𝗿𝘀𝗲: modern computer vision with HF
https://huggingface.co/learn/computer-vision-course
🦾 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗖𝗼𝘂𝗿𝘀𝗲 (𝗟𝗲𝗥𝗼𝗯𝗼𝘁): learning-based robotics
https://huggingface.co/learn/robotics-course
🧩 𝗠𝗖𝗣 𝗖𝗼𝘂𝗿𝘀𝗲: Model Context Protocol explained
https://huggingface.co/learn/mcp-course
🧪 𝗔 𝗦𝗺𝗼𝗹 𝗖𝗼𝘂𝗿𝘀𝗲: post-training AI models
https://huggingface.co/learn/a-smol-course
🕹️ 𝗠𝗟 𝗳𝗼𝗿 𝗚𝗮𝗺𝗲𝘀: AI in game development
https://huggingface.co/learn/ml-for-games-course
🧊 𝗠𝗟 𝗳𝗼𝗿 𝟯𝗗: machine learning for 3D data
https://huggingface.co/learn/ml-for-3d-course
📘 𝗢𝗽𝗲𝗻-𝗦𝗼𝘂𝗿𝗰𝗲 𝗔𝗜 𝗖𝗼𝗼𝗸𝗯𝗼𝗼𝗸: practical AI notebooks
https://huggingface.co/learn/cookbook
All of them can be found here: https://huggingface.co/learn
Post
721
Following up on LLaDA 2.0 , the paper is now out on Daily Papers🔥
It has sparked a lot of discussion in the community for showing how discrete diffusion LLMs can scale to 100B and run faster than traditional AR models.
LLaDA2.0: Scaling Up Diffusion Language Models to 100B (2512.15745)
It has sparked a lot of discussion in the community for showing how discrete diffusion LLMs can scale to 100B and run faster than traditional AR models.
LLaDA2.0: Scaling Up Diffusion Language Models to 100B (2512.15745)
sergiopaniego
posted
an
update
19 days ago
Post
1831
Google DeepMind releases FunctionGemma, a 240M model specialized in 🔧 tool calling, built for fine-tuning
TRL has day-0 support. To celebrate, we’re sharing 2 new resources:
> Colab guide to fine-tune it for 🌐 browser control with BrowserGym OpenEnv
> Standalone training script
> Colab notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_functiongemma_browsergym_openenv.ipynb
> Training script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/browsergym_llm.py (command to run it inside the script)
> More notebooks in TRL: https://huggingface.co/docs/trl/example_overview#notebooks
TRL has day-0 support. To celebrate, we’re sharing 2 new resources:
> Colab guide to fine-tune it for 🌐 browser control with BrowserGym OpenEnv
> Standalone training script
> Colab notebook: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_functiongemma_browsergym_openenv.ipynb
> Training script: https://github.com/huggingface/trl/blob/main/examples/scripts/openenv/browsergym_llm.py (command to run it inside the script)
> More notebooks in TRL: https://huggingface.co/docs/trl/example_overview#notebooks
Post
2861
Nvidia is on a roll lately. Nemotron 3 Nano is my new fav local model, but here's the real flex: they published the entire evaluation setup. Configs, prompts, logs, all of it. This is how you do open models 🔥
https://huggingface.co/blog/nvidia/nemotron-3-nano-evaluation-recipe
https://huggingface.co/blog/nvidia/nemotron-3-nano-evaluation-recipe
akhaliq
submitted
a
paper
to Daily Papers
21 days ago
Post
4577
Finch 💰 an enterprise-grade benchmark that measures whether AI agents can truly handle real world finance & accounting work.
FinWorkBench/Finch
✨ Built from real enterprise data (Enron + financial institutions), not synthetic tasks
✨ Tests end-to-end finance workflows
✨ Multimodal & cross-file reasoning
✨ Expert annotated (700+ hours) and genuinely challenging hard
FinWorkBench/Finch
✨ Built from real enterprise data (Enron + financial institutions), not synthetic tasks
✨ Tests end-to-end finance workflows
✨ Multimodal & cross-file reasoning
✨ Expert annotated (700+ hours) and genuinely challenging hard
AdinaY
authored
a
paper
21 days ago