langchain.embeddings.modelscope_hub.ModelScopeEmbeddings¶

class langchain.embeddings.modelscope_hub.ModelScopeEmbeddings(*, embed: Any = None, model_id: str = 'damo/nlp_corom_sentence-embedding_english-base')[source]¶

Bases: BaseModel, Embeddings

ModelScopeHub embedding models.

To use, you should have the modelscope python package installed.

Example

from langchain.embeddings import ModelScopeEmbeddings
model_id = "damo/nlp_corom_sentence-embedding_english-base"
embed = ModelScopeEmbeddings(model_id=model_id)

Initialize the modelscope

param embed: Any = None¶
param model_id: str = 'damo/nlp_corom_sentence-embedding_english-base'¶

Model name to use.

embed_documents(texts: List[str]) → List[List[float]][source]¶

Compute doc embeddings using a modelscope embedding model.

Parameters

texts – The list of texts to embed.

Returns

List of embeddings, one for each text.

embed_query(text: str) → List[float][source]¶

Compute query embeddings using a modelscope embedding model.

Parameters

text – The text to embed.

Returns

Embeddings for the text.

model Config[source]¶

Bases: object

Configuration for this pydantic object.

extra = 'forbid'¶

Examples using ModelScopeEmbeddings¶