Implementation for FP8/INT8 Rollout for RL training without performence drop.
Train reinforcement learning models quickly using advanced techniques without losing performance.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeImplementation for FP8/INT8 Rollout for RL training without performence drop.
Flash-RL has 306 stars on GitHub. It has been forked 23 times. Flash-RL is written mainly in Python. It has been in active development since 2025. Flash-RL is available under the MIT license. Its main topics are reinforcement-learning, vllm.
Implementation for FP8/INT8 Rollout for RL training without performence drop.
Flash-RL is an open-source project. It is released under the MIT license.
Yes. Flash-RL is free and open source — you can use, modify and self-host it.
Flash-RL is available under the MIT license.
Flash-RL is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/yaof20-flash-rl.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.