Note_rl
Reinforcement learning library for Keras and PyTorch.
Note_rl launched on October 19, 2025 with 1 votes. The site was still online in September 2026, 1 year on.
What it does
Note_rl is an efficient and flexible reinforcement learning library that allows developers to easily build and train agents. It enables developers to easily perform distributed training.
Reinforcement learning library for Keras and PyTorch. - NoteDance/Note_rl
Does a similar job
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ART – a new open-source RL framework for training agents2025 · github.com · ▲116Hey HN, I wanted to share a new project we've been working on for the last couple of months called ART (https://github.com/OpenPipe/ART). ART is a new open-source framework for training agents using reinforcement learning (RL). RL allows you to train an agent to perform better at any task whose outcome can be measured and quantified. There are many excellent projects focused on training LLMs with RL, such as GRPOTrainer (https://huggingface.co/docs/trl/main/en/grpo_trainer) and verl…
Note2025 · github.com · ▲7Machine learning library, Distributed training, Deep learning, Reinforcement learning, Models, TensorFlow, PyTorch - NoteDance/Note
LeanRL: Fast PyTorch RL with Torch.compile and CUDA Graphs2024 · github.com · ▲53We're excited to announce that we've open-sourced LeanRL, a lightweight PyTorch reinforcement learning library that provides recipes for fast RL training using torch.compile and CUDA graphs. By leveraging these tools, we've achieved significant speed-ups compared to the original CleanRL implementations - up to 6x faster! Reinforcement learning is notoriously CPU-bound due to the high frequency of small CPU operations. PyTorch's powerful compiler can help alleviate these issues, but comes with its own costs. LeanRL addresses this challenge by providing simple recipes to accelerate your…
I RL-trained an agent that trains models with RL (for ~$1.3k)Jul 2026 · github.com · ▲107RL-training an AI agent to RL-train AI agents. Contribute to Danau5tin/ai-trains-ai development by creating an account on GitHub.
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