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PaLM-rlhf-pytorch is a PyTorch implementation of Pathways Language Model (PaLM) with Reinforcement Learning from Human Feedback (RLHF). It is designed for fine-tuning large-scale language models with human preference alignment, similar to OpenAI’s approach for training models like ChatGPT.
Features
- Implements RLHF for fine-tuning large-scale language models
- Uses PPO (Proximal Policy Optimization) for reinforcement learning stability
- Optimized for training on distributed hardware like GPUs and TPUs
- Supports both pretraining and reward model fine-tuning
- Built on PyTorch with modular and extensible components
- Designed for experimenting with human-aligned AI training
Project Samples
Categories
Reinforcement Learning FrameworksLicense
MIT LicenseFollow PaLM + RLHF - Pytorch
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