This is the Linux app named Cosmos-RL whose latest release can be downloaded as v0.4.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
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Cosmos-RL
DESCRIPTION
Cosmos-RL is a scalable reinforcement learning framework designed specifically for physical AI systems such as robotics, autonomous agents, and multimodal models. It provides a distributed training architecture that separates policy learning and environment rollout processes, enabling efficient and asynchronous reinforcement learning at scale. The framework supports multiple parallelism strategies, including tensor, pipeline, and data parallelism, allowing it to leverage large GPU clusters effectively. It is built with compatibility in mind, supporting popular model families such as LLaMA, Qwen, and diffusion-based world models, as well as integration with Hugging Face ecosystems. cosmos-rl also includes support for advanced RL algorithms, low-precision training, and fault-tolerant execution, making it suitable for large-scale production workloads.
Features
- Distributed reinforcement learning with asynchronous architecture
- Support for multiple parallelism strategies including tensor and pipeline
- Compatibility with LLMs, vision-language models, and diffusion models
- Low-precision training support such as FP8 and FP4
- Fault-tolerant and elastic distributed execution
- Integration with PyTorch and Hugging Face ecosystems
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/cosmos-rl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
