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burtenshaw
updated
a
dataset
less than a minute ago
sergiopaniego
updated
2
datasets
about 2 hours ago
Jofthomas
updated
a
dataset
about 3 hours ago
Post
2280
👉 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! 🥂
- 1 reply
sergiopaniego
posted
an
update
5 days ago
Post
2412
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
sergiopaniego
posted
an
update
8 days ago
Post
349
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
9 days ago
Post
2196
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
qgallouedec
submitted
a
paper
to Daily Papers
14 days ago
sergiopaniego
posted
an
update
15 days ago
Post
419
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
16 days ago
Post
1943
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
sergiopaniego
posted
an
update
20 days ago
Post
1837
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
sergiopaniego
posted
an
update
23 days ago
sergiopaniego
posted
an
update
26 days ago
Post
2105
🎄 last talk of the year about open AI and HF today at Universidad Rey Juan Carlos for undergrad students
always a pleasure to be back at my alma mater
🎅 slides: https://github.com/sergiopaniego/talks
always a pleasure to be back at my alma mater
🎅 slides: https://github.com/sergiopaniego/talks
- 1 reply
sergiopaniego
posted
an
update
27 days ago
Post
1680
TRL now includes agent training support for GRPO‼️
Train 🕵️ agents with 🔧 tools, enabling interaction with external functions and APIs.
And of course, a new notebook and scripts to get you up to speed
📘 notebook tutorial: https://github.com/huggingface/trl/blob/main/examples/notebooks/grpo_agent.ipynb
📂 script examples: https://github.com/huggingface/trl/blob/main/examples/scripts/grpo_agent.py
📦 TRL v0.26.0 release: https://github.com/huggingface/trl/releases/tag/v0.26.0
Train 🕵️ agents with 🔧 tools, enabling interaction with external functions and APIs.
And of course, a new notebook and scripts to get you up to speed
📘 notebook tutorial: https://github.com/huggingface/trl/blob/main/examples/notebooks/grpo_agent.ipynb
📂 script examples: https://github.com/huggingface/trl/blob/main/examples/scripts/grpo_agent.py
📦 TRL v0.26.0 release: https://github.com/huggingface/trl/releases/tag/v0.26.0
-
- 2 replies
sergiopaniego
posted
an
update
28 days ago
Post
2845
ICYMI, you can fine-tune open LLMs using Claude Code
just tell it:
“Fine-tune Qwen3-0.6B on open-r1/codeforces-cots”
and Claude submits a real training job on HF GPUs using TRL.
it handles everything:
> dataset validation
> GPU selection
> training + Trackio monitoring
> job submission + cost estimation
when it’s done, your model is on the Hub, ready to use
read more about the process: https://huggingface.co/blog/hf-skills-training
just tell it:
“Fine-tune Qwen3-0.6B on open-r1/codeforces-cots”
and Claude submits a real training job on HF GPUs using TRL.
it handles everything:
> dataset validation
> GPU selection
> training + Trackio monitoring
> job submission + cost estimation
when it’s done, your model is on the Hub, ready to use
read more about the process: https://huggingface.co/blog/hf-skills-training
- 1 reply
sergiopaniego
posted
an
update
28 days ago
Post
2270
We just released TRL v0.26.0!
It comes packed with updates:
> Agent training with tools in GRPO
> New CISPO & SAPO losses + reasoning rewards
> vLLM quantization in colocate mode
> Dataset shuffling in SFT
> Lots of NEW examples
> Tons of fixes and documentation improvements
It comes packed with updates:
> Agent training with tools in GRPO
> New CISPO & SAPO losses + reasoning rewards
> vLLM quantization in colocate mode
> Dataset shuffling in SFT
> Lots of NEW examples
> Tons of fixes and documentation improvements
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- 3 replies
sergiopaniego
posted
an
update
29 days ago
Post
2973
NEW:
@EssentialAI
just released Rnj-1, their first 8B model.
You can easily fine-tune it with GRPO using TRL to add reasoning capabilities to a compact mode
Free Colab link: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_rnj_1_instruct.ipynb
More free TRL notebooks: https://huggingface.co/docs/trl/main/en/example_overview#notebooks
You can easily fine-tune it with GRPO using TRL to add reasoning capabilities to a compact mode
Free Colab link: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_rnj_1_instruct.ipynb
More free TRL notebooks: https://huggingface.co/docs/trl/main/en/example_overview#notebooks
sergiopaniego
posted
an
update
about 1 month ago
Post
2866
Want to get started with fine-tuning but don’t know where to begin? 🤓☝️
We’re expanding our collection of beginner-friendly free Colab notebooks so you can learn and fine-tune models using TRL at no cost
🔬 Check out the full list of free notebooks: https://huggingface.co/docs/trl/main/en/example_overview#notebooks
🔬 If you want more advanced content, we also have a lot to cover in the community tutorials: https://huggingface.co/docs/trl/community_tutorials
And now the obvious question: what would you like us to add next?
We’re expanding our collection of beginner-friendly free Colab notebooks so you can learn and fine-tune models using TRL at no cost
🔬 Check out the full list of free notebooks: https://huggingface.co/docs/trl/main/en/example_overview#notebooks
🔬 If you want more advanced content, we also have a lot to cover in the community tutorials: https://huggingface.co/docs/trl/community_tutorials
And now the obvious question: what would you like us to add next?
sergiopaniego
posted
an
update
about 1 month ago
Post
2401
NEW:
@mistralai
released a fantastic family of multimodal models, Ministral 3.
You can fine-tune them for free on Colab using TRL ⚡️, supporting both SFT and GRPO
Link to the notebooks:
- SFT: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/sft_ministral3_vl.ipynb
- GRPO: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_ministral3_vl.ipynb
- TRL and more examples: https://huggingface.co/docs/trl/index
You can fine-tune them for free on Colab using TRL ⚡️, supporting both SFT and GRPO
Link to the notebooks:
- SFT: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/sft_ministral3_vl.ipynb
- GRPO: https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_ministral3_vl.ipynb
- TRL and more examples: https://huggingface.co/docs/trl/index
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-
- 2 replies