qdrant / qdrant/fastembed

[Model]: granite-embedding-107m-multilingual

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Dominant language
Python
Stars
3.2k
Forks
248
Avg merge
4d 8h
Merged PRs (30d)
4

Description

Which model would you like to support?

https://huggingface.co/ibm-granite/granite-embedding-107m-multilingual

What are the main advantages of this model?

His main advantage is his weight and the fact is multilingual. These benefits + the fact he got real good results good lead granite models suites to become on of the industry standard

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

No files, tests, or entry points are named. Start by reviewing how existing Hugging Face embedding models are integrated in fastembed, then inspect the granite-embedding-107m-multilingual model page. Done means this model is supported with the project’s expected validation and tests.

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
Needs clarification
Newbie friendliness
35/100

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