فائن ٹیوننگ، تربیت اور ڈیٹا

TRL

huggingface/trl

A library for post-training transformer models with supervised fine-tuning and preference-optimization methods.

★ 19.5Kستارے
⑂ 3.1Kفورکس
109کھلے مسائل
Pythonزبان
Apache-2.0لائسنس
Q84ادارتی اسکور

جائزہ

TRL builds on the Transformers ecosystem and provides trainers for methods such as supervised fine-tuning (SFT), direct preference optimization (DPO), and group relative policy optimization (GRPO). It supports distributed training integrations and parameter-efficient fine-tuning workflows.

اہم خصوصیات

  • SFT, DPO, GRPO and related trainers
  • Transformers ecosystem integration
  • Distributed training support
  • CLI and Python APIs

ضروریات، انسٹالیشن اور فوری آغاز

Install the Python package with `pip install trl`; follow the docs for optional Accelerate, PEFT, and hardware setup.

استعمال

Choose a trainer, prepare a compatible dataset and model, configure training arguments, then run the trainer or CLI command.

ماڈل کی مطابقت اور استعمال کے مواقع

Designed for transformer models in the Hugging Face ecosystem; architecture and hardware support depends on the chosen method and dependencies.

لائسنس اور خطرے سے متعلق نوٹس

The repository declares Apache-2.0. Dataset, base-model, and hosted service terms are separate.

ریلیز اور دیکھ بھال

See the official repository for current releases and changes.

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