TRL
Hugging Face library for training language models with RLHF, SFT, and DPO
TRL (Transformer Reinforcement Learning) is the standard Hugging Face library for fine-tuning language models. It supports supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), direct preference optimization (DPO), and other alignment techniques. Built on top of Transformers and integrates with PEFT for parameter-efficient training.
Pricing: Free
TRL Alternatives
Explore 21 products in the Fine-tuning category. View all TRL alternatives.
LLaMA-Factory
Open-source fine-tuning framework for 100+ LLMs with a web UI
Unsloth
Fine-tune LLMs up to 30x faster with 90% less memory usage
torchtune
PyTorch-native library for fine-tuning LLMs on consumer and enterprise GPUs
OVHcloud AI
European cloud provider with AI inference, training, and deployment services
Amazon Bedrock
Managed API access to foundation models on AWS with built-in fine-tuning and agent tooling
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