Fine-tune Any LLM from the Hugging Face Hub with Together AI

The pace of AI development today is breathtaking. Every single day, hundreds of new models appear on the Hugging Face Hub, some are specialized variants of popular base models like Llama or Qwen, others feature novel architectures or have been trained from scratch for specific domains. Whether it's a medical AI trained on clinical data, a coding assistant optimized for a particular programming language, or a multilingual model fine-tuned for specific cultural contexts, the Hugging Face Hub has become the beating heart of open-source AI innovation.

But here's the challenge: finding an amazing model is just the beginning. What happens when you discover a model that's 90% perfect for your use case, but you need that extra 10% of customization? Traditional fine-tuning infrastructure is complex, expensive, and often requires significant DevOps expertise to set up and maintain.

This is exactly the gap that Together AI and Hugging Face are bridging today. We're announcing a powerful new capability that makes the entire Hugging Face Hub available for fine-tuning using Together AI's infrastructure. Now, any compatible LLM on the Hub, whether it's from Meta or an individual contributor, can be fine-tuned with the same ease and reliability you expect from Together's platform.🚀

Getting Started in 5 Minutes

Here's all it takes to start fine-tuning a HF model on the Together AI platform:

That's it! Your model will be trained on Together's infrastructure and can be deployed for inference, downloaded or even uploaded back to the Hub! For private repositories, simply add your HF token with hf_api_token="hf_xxxxxxxxxxxx".

How It Works:

As seen in the example above, when you fine-tune a Hugging Face model on Together AI, you actually specify two models:

In general, all CausalLM models under 100B params are intended to work. For a comprehensive walkthrough on how to choose base and custom models and much more, read our full guide!