In the news
Together AI expands fine-tuning service with more models, live metrics, and finer controls
Together AI · Published · 3 min read
In 30 seconds
- What happened
- Together AI expanded its fine-tuning service with new open-weight models, live experiment tracking, expert LoRA adapters, early stopping, and price cuts up to 70 percent.
- Why it matters
- Engineers fine-tuning open-source models need visibility into training progress, control over which model layers to adapt, and cost-effective ways to iterate on experiments.
- Watch out
- Expert LoRA adapters only benefit mixture-of-experts models. Early stopping requires a validation set. Sequence packing behavior changes may affect small datasets differently than large ones.
- fine-tun
- lora
- token
- open-weight
The patterns behind this
- Progressive Rollout & Shadow Mode
- Context Editing & Tool-Result Clearing
- Agent Observability & Tracing
Each one covers how the technique works, when it earns its cost, and where it breaks.
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