| <div align="center"> | |
| <img src="logo.svg" alt="RLinf-logo" width="500"/> | |
| </div> | |
| <div align="center"> | |
| <a href="https://github.com/RLinf/RLinf"><img src="https://img.shields.io/badge/Github-blue"></a> | |
| <a href="https://rlinf.readthedocs.io/en/latest/"><img src="https://img.shields.io/badge/Documentation-Purple?color=8A2BE2&logo=readthedocs"></a> | |
| </div> | |
| <h1 align="center">RLinf: Reinforcement Learning Infrastructure for Agentic AI</h1> | |
| [RLinf](https://github.com/RLinf/RLinf) is a flexible and scalable open-source infrastructure designed for post-training foundation models (LLMs, VLMs, VLAs) via reinforcement learning. The 'inf' in RLinf stands for Infrastructure, highlighting its role as a robust backbone for next-generation training. It also stands for Infinite, symbolizing the system’s support for open-ended learning, continuous generalization, and limitless possibilities in intelligence development. | |
| <div align="center"> | |
| <img src="overview.png" alt="RLinf-overview" width="600"/> | |
| </div> | |
| ## Model Description | |
| This repository provides a PyTorch ResNet-10 pretrained checkpoint, converted from the original JAX implementation released by the [SeRL](https://github.com/rail-berkeley/serl) project. | |
| The original JAX weights can be found here: | |
| https://github.com/rail-berkeley/serl/releases/download/resnet10/resnet10_params.pkl | |
| Within RLinf, this checkpoint is used as the pretrained CNN ResNet encoder for real-world embodied learning experiments. | |
| ## How to Use | |
| Please integrate the provided model with the [RLinf](https://github.com/RLinf/RLinf) codebase. To do so, modify the ``extra_config.pretrained_ckpt_path`` as the path for this model in the configuration file ``examples/embodiment/config/model/cnn_policy.yaml``. | |
| ## License | |
| This code repository and the model weights are licensed under the MIT License. | |