Cloud Model Trainer

关于

Effortlessly train and fine-tune language models on Hugging Face's managed cloud infrastructure without needing a local GPU. This skill streamlines the process using Transformer Reinforcement Learning (TRL), supporting methods like Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO). It automates job submission, provides real-time monitoring, ensures trained models are saved directly to the Hub, and can even convert them to GGUF for local deployment, making it ideal for any cloud-based training task.

主要功能

• Submits training jobs to run on managed Hugging Face cloud GPU infrastructure.
• Includes real-time monitoring integration with Trackio.
• Supports various TRL training methods including SFT, DPO, GRPO, and Reward Modeling.
• Provides guidance on dataset preparation, hardware selection, and cost estimation.
• Automates model conversion to GGUF format for local deployment.
• 605 GitHub stars

使用场景

• Fine-tuning a language model on a specific dataset without a local GPU.
• Running a DPO (Direct Preference Optimization) training job on the cloud.
• Training a model and converting it to GGUF for use with Ollama or LM Studio.