[ENH] Add optional kwargs when initialising SentenceTransformerEmbedd…

…ingFunction class (#1891)

## Description of changes  
  
*Summarize the changes made by this PR.*  
 - Improvements & Bug fixes  
- Add optional kwargs for `SetenceTransformer` when initialising
`SentenceTransformerEmbeddingFunction` class (Issue
[#1857](#1857))
  
## Test plan  
*How are these changes tested?*  
  
- [x] Tests pass locally with `pytest` for python
- installing chroma as an editable package locally and testing with the
code
	```python
	import chromadb
	from chromadb.utils import embedding_functions
sentence_transformer_ef =
embedding_functions.SentenceTransformerEmbeddingFunction(prompts={"query":
"query: ", "passage": "passage: "})
	print(sentence_transformer_ef.models['all-MiniLM-L6-v2'].prompts)
	```
	returned
	```bash
	{'query': 'query: ', 'passage': 'passage: '}
	```
	 
## Documentation Changes  
*Are all docstrings for user-facing APIs updated if required? Do we need
to make documentation changes in the [docs
repository](https://github.com/chroma-core/docs)?*
I have added the documentation for
`SentenceTransformerEmbeddingFunction` initialisation.

Co-authored-by: sumaiyah <o##wJdTOvNkIC!1R@bQO>

chromadb/utils/embedding_functions.py

@@ -61,15 +61,24 @@ def __init__(
         model_name: str = "all-MiniLM-L6-v2",
         device: str = "cpu",
         normalize_embeddings: bool = False,
+        **kwargs: Any
     ):
+        """Initialize SentenceTransformerEmbeddingFunction.
+
+        Args:
+            model_name (str, optional): Identifier of the SentenceTransformer model, defaults to "all-MiniLM-L6-v2"
+            device (str, optional): Device used for computation, defaults to "cpu"
+            normalize_embeddings (bool, optional): Whether to normalize returned vectors, defaults to False
+            **kwargs: Additional arguments to pass to the SentenceTransformer model.
+        """
         if model_name not in self.models:
             try:
                 from sentence_transformers import SentenceTransformer
             except ImportError:
                 raise ValueError(
                     "The sentence_transformers python package is not installed. Please install it with `pip install sentence_transformers`"
                 )
-            self.models[model_name] = SentenceTransformer(model_name, device=device)
+            self.models[model_name] = SentenceTransformer(model_name, device=device, **kwargs)
         self._model = self.models[model_name]
         self._normalize_embeddings = normalize_embeddings