Spaces:
Paused
Paused
File size: 5,844 Bytes
2f5127c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
<div style="text-align: center">
<img src="https://huggingface.co/datasets/trl-lib/documentation-images/resolve/main/trl_banner_dark.png">
</div>
# TRL - Transformer Reinforcement Learning
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).
You can also explore TRL-related models, datasets, and demos in the [TRL Hugging Face organization](https://huggingface.co/trl-lib).
## Learn
Learn post-training with TRL and other libraries in 🤗 [smol course](https://github.com/huggingface/smol-course).
## Contents
The documentation is organized into the following sections:
- **Getting Started**: installation and quickstart guide.
- **Conceptual Guides**: dataset formats, training FAQ, and understanding logs.
- **How-to Guides**: reducing memory usage, speeding up training, distributing training, etc.
- **Integrations**: DeepSpeed, Liger Kernel, PEFT, etc.
- **Examples**: example overview, community tutorials, etc.
- **API**: trainers, utils, etc.
## Blog posts
<div class="mt-10">
<div class="w-full flex flex-col space-y-4 md:space-y-0 md:grid md:grid-cols-2 md:gap-y-4 md:gap-x-5">
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/vllm-colocate">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/vllm-colocate/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on June 3, 2025</p>
<p class="text-gray-700">NO GPU left behind: Unlocking Efficiency with Co-located vLLM in TRL</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/liger-grpo">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/liger-grpo/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on May 25, 2025</p>
<p class="text-gray-700">🐯 Liger GRPO meets TRL</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/open-r1">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/open-r1/thumbnails.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on January 28, 2025</p>
<p class="text-gray-700">Open-R1: a fully open reproduction of DeepSeek-R1</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/dpo_vlm">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/dpo_vlm/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on July 10, 2024</p>
<p class="text-gray-700">Preference Optimization for Vision Language Models with TRL</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/putting_rl_back_in_rlhf_with_rloo">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/putting_rl_back_in_rlhf_with_rloo/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on June 12, 2024</p>
<p class="text-gray-700">Putting RL back in RLHF</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/trl-ddpo">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/166_trl_ddpo/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on September 29, 2023</p>
<p class="text-gray-700">Finetune Stable Diffusion Models with DDPO via TRL</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/dpo-trl">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/157_dpo_trl/dpo_thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on August 8, 2023</p>
<p class="text-gray-700">Fine-tune Llama 2 with DPO</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/stackllama">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/138_stackllama/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on April 5, 2023</p>
<p class="text-gray-700">StackLLaMA: A hands-on guide to train LLaMA with RLHF</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/trl-peft">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/133_trl_peft/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on March 9, 2023</p>
<p class="text-gray-700">Fine-tuning 20B LLMs with RLHF on a 24GB consumer GPU</p>
</a>
<a class="!no-underline border dark:border-gray-700 p-5 rounded-lg shadow hover:shadow-lg" href="https://huggingface.co/blog/rlhf">
<img src="https://raw.githubusercontent.com/huggingface/blog/main/assets/120_rlhf/thumbnail.png" alt="thumbnail" class="mt-0">
<p class="text-gray-500 text-sm">Published on December 9, 2022</p>
<p class="text-gray-700">Illustrating Reinforcement Learning from Human Feedback</p>
</a>
</div>
</div>
|