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19 changes: 19 additions & 0 deletions docs/source/index.md
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TRL is a full stack library where we provide a set of tools to train transformer language models with methods like Supervised Fine-Tuning (SFT), Group Relative Policy Optimization (GRPO), Direct Preference Optimization (DPO), Reward Modeling, and more.
The library is integrated with 🤗 [transformers](https://github.com/huggingface/transformers).

<div class="mt-10">
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/sft_ministral3_vl.ipynb">
<img src="https://pbs.twimg.com/media/G7QgGdCXgAAesMG?format=jpg&name=small" alt="thumbnail" class="mt-0">
<p class="text-gray-700">Supervised Fine-Tuning (SFT) Ministral-3 with QLoRA</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/grpo_ministral3_vl.ipynb">
<img src="https://pbs.twimg.com/media/G7QgGdCXgAAesMG?format=jpg&name=small" alt="thumbnail" class="mt-0">
<p class="text-gray-700">GRPO Ministral-3 with QLoRA</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/docs/trl/main/en/openenv">
<img src="https://pbs.twimg.com/media/G6geuwEXEAA9ngv?format=jpg&name=small" alt="thumbnail" class="mt-0">
<p class="text-gray-700">OpenEnv Integration Guide</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://colab.research.google.com/github/huggingface/trl/blob/main/examples/notebooks/openenv_wordle_grpo.ipynb">
<img src="https://pbs.twimg.com/media/G6geuwEXEAA9ngv?format=jpg&name=small" alt="thumbnail" class="mt-0">
<p class="text-gray-700">OpenEnv Wordle with GRPO</p>
</a>
</div>

## 🎉 What's New

**OpenEnv Integration:** TRL now supports **[OpenEnv](https://huggingface.co/blog/openenv)**, the open-source framework from Meta for defining, deploying, and interacting with environments in reinforcement learning and agentic workflows.
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