Overview
Description
Get better results from your AI models by fine-tuning them with reinforcement learning — the same technique used to train DeepSeek-R1. TRL provides ready-to-use trainers for the most effective alignment methods (DPO, GRPO, SFT) so you don't need a PhD team to do it. Scale from a single GPU to a multi-node cluster with just a few lines of code.
Technical scorecard
License
Apache-2.0
Commercial use
Yes
OpenAI-compatible API
No
REST API
No
Fine-tuning support
No
Quantization support
No
Docker available
Yes
GUI / no-code available
No
Telemetry
Unknown
Offline after setup
No
Data & Privacy
Does it send data online?
This listing is not marked offline after setup.
Does it store history?
Not verified in this directory yet. Review the upstream docs for persistence, logs, and workspace storage.
License checks?
Commercial use is marked as allowed or likely allowed by the listed license.
Telemetry?
Unknown
Last verified: Jul 22, 2026. Maintainer verification should be treated as directory guidance, not legal advice.
Deploying TRL in production?
Stop silent telemetry leaks before they trigger an unintended data leak. Get our Airgap Certainty Blueprint for TRL.
Request Privacy and Telemetry AuditSetup & Installation
A developer can usually get this running with standard docs.
# Start with the official project repository
# https://github.com/huggingface/trlHardware Requirements
Works Well With