This is the Linux app named verl whose latest release can be downloaded as v0.6.1sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named verl with OnWorks for free.
请按照以下说明运行此应用程序：
- 1. 在您的 PC 中下载此应用程序。
- 2. 在我们的文件管理器 https://www.onworks.net/myfiles.php?username=XXXXX 中输入您想要的用户名。
- 3. 在这样的文件管理器中上传这个应用程序。
- 4. 从此网站启动OnWorks Linux online 或Windows online emulator 或MACOS online emulator。
- 5. 从您刚刚启动的 OnWorks Linux 操作系统，使用您想要的用户名转到我们的文件管理器 https://www.onworks.net/myfiles.php?username=XXXXX。
- 6. 下载应用程序，安装并运行。
SCREENSHOTS
Ad
真实
商品描述
VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy. It ships with reference implementations of popular alignment algorithms and clear examples that make it straightforward to reproduce baselines before customizing. Data pipelines treat human feedback, simulated environments, and synthetic preferences as interchangeable sources, which helps with rapid experimentation. VERL is meant for both research and production hardening: logging, checkpointing, and evaluation suites are built in so you can track learning dynamics and regressions over time.
特征
- Unified pipeline for SFT, preference modeling, and online RL
- Distributed training with mixed precision and efficient replay buffers
- Reference implementations of popular alignment/RL algorithms
- Pluggable data sources for human, simulated, and synthetic feedback
- Comprehensive logging, checkpoints, and eval dashboards
- Extensible components for custom rewards, policies, and environments
程式语言
Python
分类
This is an application that can also be fetched from https://sourceforge.net/projects/verl.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
