Fine-Tuning Platform Upgrades: Larger Models, Longer Contexts, Enhanced Hugging Face Integrations

This post details the expansion of the Together Fine-Tuning Platform to support training of models with over 100B parameters, including specific families like DeepSeek-R1, Qwen3-235B, and Llama 4 Maverick. It also introduces significant increases in maximum supported context lengths for various models, with some reaching up to 131k tokens, achieved through overhauls of training systems. A key new integration is the ability to fine-tune models directly from and upload checkpoints to the Hugging Face Hub. Additionally, the platform now supports advanced DPO variants (LN-DPO, DPO+NLL, SimPO) and the `batch_size="max"` convenience option for API and Python client jobs.