qdrant / qdrant/fastembed

how could fastembed load the local model?

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Python
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Description

since hf connection is not stable, I pre-download all the models needed in the local environment, how could I use the api to load these models ?

embedding_model = TextEmbedding(model_name='/root/.cache/modelscope/hub/models/BAAI/bge-small-en-v1.5')

but got an error saying

Traceback (most recent call last):
  File "/usr/opt/nky-ai/chat-agent/test.py", line 11, in <module>
    embedding_model = TextEmbedding(model_name='/root/.cache/modelscope/hub/models/BAAI/bge-small-en-v1.5') 
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/root/miniconda3/lib/python3.12/site-packages/fastembed/text/text_embedding.py", line 126, in __init__
    raise ValueError(
ValueError: Model /root/.cache/modelscope/hub/models/BAAI/bge-small-en-v1.5 is not supported in TextEmbedding. Please check the supported models using `TextEmbedding.list_supported_models()`

any idea ?

Contributor guide

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First steps

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start at the Python TextEmbedding constructor and the list_supported_models() entry point mentioned in the report. Check how model_name paths are validated and whether the local ModelScope path can be accepted; done means the supported local-loading behavior is clear and works for the reported model path.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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