Together AI has joined forces with Adaption, a startup focused on AI data optimization, to integrate its fine-tuning platform directly into Adaption’s offering. This collaboration aims to accelerate the creation of customized open-source AI models.
Adaption, co-founded by former Cohere and Google DeepMind leaders Sara Hooker and Sudip Roy, provides tools for analyzing dataset structure, adapting examples, and evaluating data quality, reporting an average 82% increase in data quality for early users.
With this new integration, users of Adaption’s platform can connect their Together AI accounts to seamlessly transition from data optimization to model fine-tuning. The workflow allows users to refine their training datasets within Adaption and then initiate fine-tuning jobs on Together AI’s infrastructure, leveraging optimized hyperparameters.
Sara Hooker, Co-founder & CEO of Adaption, stated, "Together Fine-Tuning gives Adaptive Data users the infrastructure to turn shaped datasets into stronger, more reliable open models." The platform supports various fine-tuning methods like LoRA and full fine-tuning, along with large models exceeding 100 billion parameters.
Together AI’s fine-tuning service offers features such as cost estimation before training, real-time progress tracking, and direct model export to Hugging Face Hub, aiming to simplify the process for developers and researchers.
Seamless Workflow
This partnership allows datasets optimized by Adaption to flow directly into Together Fine-Tuning workflows, bridging the gap between data preparation and model specialization.
