Together Fine-Tuning Platform, Now With Preference Optimization and Continued Training

Together AI has introduced a new platform for fine-tuning language models, enabling businesses to easily refine and improve their models based on user preferences and fresh data. The platform supports preference optimization and continued training, allowing developers to fine-tune open-weight models like Llama or Gemma to reflect users' expectations and capture domain specifics. With the introduction of a new web UI, developers can now start fine-tuning runs directly from the browser, making it more accessible for those without extensive technical knowledge. The platform also includes Direct Preference Optimization, which trains language models on preference data that does not involve an additional reward model. Additionally, the platform supports continued training, allowing developers to update their existing models with new data and adapt them as their app evolves. Other improvements include support for training top-ranking open models, message weights, and learning rate schedulers, as well as optimized data preprocessing logic. The pricing has also been updated to make it more transparent and lower, with no minimum price for fine-tuning. Overall, the platform aims to empower developers and businesses to continuously evolve their models with full ownership.

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