Correct prompt for fastchat-t5-3b-v1.0 in the case of RAG
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Description
Hi,
Willing to use the `fastchat-t5-3b-v1.0` model for RAG or Retrieval Augmented Generation (Q&A based on retrieved documents or context), I tried many prompts based on FastChat code but never managed to obtain a good answer following these criteria:
- Detailed answer with no hallucinations (repeated strings)
- The model has to answer 'I don't know' if the answer cannot be determined from the provided context
Does anyone has an advice for using `fastchat-t5-3b-v1.0` for RAG?
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No file, test, or entry point is named; begin by reviewing FastChat's prompt handling and the fastchat-t5-3b-v1.0 usage for retrieval-augmented question answering. The issue would be done only when a validated prompt or documented guidance produces grounded answers and responds with "I don't know" when the context is insufficient.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- ai
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 15/100