qdrant / qdrant/fastembed

Add Support to stella-en-400M-v5

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#332 1 comment 3 reactions 0 assignees View on GitHub

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

Reqest to support for Embedding Model for Efficient Vector Search

Add Support to https://huggingface.co/dunzhang/stella_en_400M_v5

What Python version are you on? e.g. python --version

3.10

Version

0.2.7 (Latest)

What os are you seeing the problem on?

Windows

Relevant stack traces and/or logs

No response

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 by reviewing fastembed's existing embedding-model integration and the Hugging Face page for dunzhang/stella_en_400M_v5. Identify the model-specific support points and any relevant validation or test commands in the repository. Done means the model can be selected and used for embedding generation and efficient vector search on the reported Python and Windows setup.

Written by the indexing model from the issue text.

Assessment

Tech stack
huggingface, python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Mostly clear
Newbie friendliness
35/100

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