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This PR add an embeddings integration for model2vec, the `Model2vecEmbeddings` class. - **Description**: [Model2Vec](https://github.com/MinishLab/model2vec) lets you turn any sentence transformer into a really small static model and makes running the model faster. - **Issue**: - **Dependencies**: model2vec ([pypi](https://pypi.org/project/model2vec/)) - **Twitter handle:**: - [x] **Add tests and docs**: - [Test](https://github.com/blacksmithop/langchain/blob/model2vec_embeddings/libs/community/langchain_community/embeddings/model2vec.py), [docs](https://github.com/blacksmithop/langchain/blob/model2vec_embeddings/docs/docs/integrations/text_embedding/model2vec.ipynb) - [x] **Lint and test**: --------- Co-authored-by: Abhinav KM <abhinav.m@zerone-consulting.com> Co-authored-by: Bagatur <baskaryan@gmail.com>
12 lines
394 B
Python
12 lines
394 B
Python
from langchain_community.embeddings.model2vec import Model2vecEmbeddings
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def test_hugginggface_inferenceapi_embedding_documents_init() -> None:
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"""Test model2vec embeddings."""
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try:
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embedding = Model2vecEmbeddings("minishlab/potion-base-8M")
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assert len(embedding.embed_query("hi")) == 256
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except Exception:
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# model2vec is not installed
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assert True
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