qdrant / qdrant/fastembed

[Model]: s2593817/sft-sql-embedding

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Dominant language
Python
Stars
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Forks
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Avg merge
4d 8h
Merged PRs (30d)
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Description

Which model would you like to support?

https://huggingface.co/s2593817/sft-sql-embedding

What are the main advantages of this model?

State of the art model in a RAG system for SQL databases

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the Hugging Face model page for s2593817/sft-sql-embedding and inspect FastEmbed’s existing model-support entry points for comparable embedding models. Done means this SQL-focused embedding model is supported and usable in a RAG system for SQL databases, with the relevant checks passing.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
48/100

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