Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.
日本語の概要は準備中です。原文の説明を表示しています。
Add or review a paper entry in TRL's paper index. Use when a PR implements a method, algorithm, or training approach from a research paper, or when reviewing such a PR.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Any PR that implements a method, algorithm, or training approach from a research paper must add a corresponding subsection to docs/source/paper_index.md. When reviewing such a PR, check that the file was updated.
The file is organized as one ## section per method family (usually one per trainer), each holding ### subsections, one per paper.
Each entry contains:
### heading.**📜 Paper**: https://huggingface.co/papers/<id>
from trl import GRPOConfig, GRPOTrainer
training_args = GRPOConfig(
beta=0.001, # "the KL coefficient to 0.001"
num_generations=16, # "For each question, we sample 16 outputs..."
)
When the paper doesn't specify hyperparameters, say so in a comment rather than inventing values.## section.## section with a one-line pointer to the trainer, e.g. Papers relating to the [GRPOTrainer].まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Post-train LLMs with TRL (Transformers Reinforcement Learning) — SFT, DPO, GRPO, KTO, and reward-model training. Use when writing or debugging training code with the TRL Python API or the trl CLI.
日本語の概要は準備中です。原文の説明を表示しています。