add model_revison parameter to ModelScopeEmbeddings (langchain-ai#8669)

---------

Co-authored-by: Bagatur <[email protected]>

libs/langchain/langchain/embeddings/modelscope_hub.py

@@ -1,4 +1,4 @@
-from typing import Any, List
+from typing import Any, List, Optional
 
 from pydantic import BaseModel, Extra
 
@@ -15,27 +15,30 @@ class ModelScopeEmbeddings(BaseModel, Embeddings):
 
             from langchain.embeddings import ModelScopeEmbeddings
             model_id = "damo/nlp_corom_sentence-embedding_english-base"
-            embed = ModelScopeEmbeddings(model_id=model_id)
+            embed = ModelScopeEmbeddings(model_id=model_id, model_revision="v1.0.0")
     """
 
     embed: Any
     model_id: str = "damo/nlp_corom_sentence-embedding_english-base"
     """Model name to use."""
+    model_revision: Optional[str] = None
 
     def __init__(self, **kwargs: Any):
         """Initialize the modelscope"""
         super().__init__(**kwargs)
         try:
             from modelscope.pipelines import pipeline
             from modelscope.utils.constant import Tasks
-
-            self.embed = pipeline(Tasks.sentence_embedding, model=self.model_id)
-
         except ImportError as e:
             raise ImportError(
                 "Could not import some python packages."
                 "Please install it with `pip install modelscope`."
             ) from e
+        self.embed = pipeline(
+            Tasks.sentence_embedding,
+            model=self.model_id,
+            model_revision=self.model_revision,
+        )
 
     class Config:
         """Configuration for this pydantic object."""