HuggingFace Introduces TextEnvironments: An Orchestrator between a Machine Learning Model and A Set of Tools (Python Functions) that the Model can Call to Solve Specific Tasks

Supervised Fine-tuning (SFT), Reward Modeling (RM), and Proximal Policy Optimization (PPO) are all part of TRL. In this full-stack library, researchers give tools to train transformer language models and stable diffusion models with Reinforcement Learning. The library is an extension of Hugging Face’s transformers collection. Therefore, language models can be loaded directly via transformers after […]

The post HuggingFace Introduces TextEnvironments: An Orchestrator between a Machine Learning Model and A Set of Tools (Python Functions) that the Model can Call …

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