community[minor]: Add support for modle2vec embeddings (#28507)

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>

libs/community/tests/unit_tests/embeddings/test_imports.py

@@ -26,6 +26,7 @@ EXPECTED_ALL = [
     "MlflowAIGatewayEmbeddings",
     "MlflowEmbeddings",
     "MlflowCohereEmbeddings",
+    "Model2vecEmbeddings",
     "ModelScopeEmbeddings",
     "TensorflowHubEmbeddings",
     "SagemakerEndpointEmbeddings",

libs/community/tests/unit_tests/embeddings/test_model2vec.py

@@ -0,0 +1,11 @@
+from langchain_community.embeddings.model2vec import Model2vecEmbeddings
+
+
+def test_hugginggface_inferenceapi_embedding_documents_init() -> None:
+    """Test model2vec embeddings."""
+    try:
+        embedding = Model2vecEmbeddings("minishlab/potion-base-8M")
+        assert len(embedding.embed_query("hi")) == 256
+    except Exception:
+        # model2vec is not installed
+        assert True