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aifeatures.ai
Teams training a domain model instead of RAG-only

The open-weight fine-tune stack

LangChain builds the JSONL, Together runs the LoRA, Hugging Face stores weights. Not a live helpdesk.

Who owns what

  1. LangChain

    The dataset — pairs from your docs. Not the GPU job.

    Try LangChain (opens in a new tab)

  2. Together AI

    The train and the endpoint. Not the Hub registry.

    Try Together AI (opens in a new tab)

  3. Hugging Face

    The registry — base, split, adapter. Not the live chain.

    Try Hugging Face (opens in a new tab)

How to use this stack

  1. LangChain turns internal docs into input/output pairs. Validate the JSONL before you spend GPU.
  2. Push the split to Hugging Face Hub.
  3. Together fine-tunes LoRA on a Hub base. Swap Together for Replicate if that is the cluster.
  4. Write the adapter back to Hugging Face. Serve from Together.
  5. This is not the enterprise RAG router. That one answers from Pinecone without training.