docs: HFEmbeddings: Add more information to model_kwargs/encode_kwargs (#19594)

- **Description:** Be more explicit with the `model_kwargs` and
`encode_kwargs` for `HuggingFaceEmbeddings`.
    - **Issue:** -
    - **Dependencies:** -

I received some reports by my users that they didn't realise that you
could change the default `batch_size` with `HuggingFaceEmbeddings`,
which may be attributed to how the `model_kwargs` and `encode_kwargs`
don't give much information about what you can specify.

I've added some parameter names & links to the Sentence Transformers
documentation to help clear it up. Let me know if you'd rather have
Markdown/Sphinx-style hyperlinks rather than a "bare URL".

- Tom Aarsen

libs/community/langchain_community/embeddings/huggingface.py

@@ -44,9 +44,14 @@ class HuggingFaceEmbeddings(BaseModel, Embeddings):
     """Path to store models. 
     Can be also set by SENTENCE_TRANSFORMERS_HOME environment variable."""
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
-    """Keyword arguments to pass to the model."""
+    """Keyword arguments to pass to the Sentence Transformer model, such as `device`,
+    `prompts`, `default_prompt_name`, `revision`, `trust_remote_code`, or `token`.
+    See also the Sentence Transformer documentation: https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer"""
     encode_kwargs: Dict[str, Any] = Field(default_factory=dict)
-    """Keyword arguments to pass when calling the `encode` method of the model."""
+    """Keyword arguments to pass when calling the `encode` method of the Sentence
+    Transformer model, such as `prompt_name`, `prompt`, `batch_size`, `precision`,
+    `normalize_embeddings`, and more.
+    See also the Sentence Transformer documentation: https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer.encode"""
     multi_process: bool = False
     """Run encode() on multiple GPUs."""
     show_progress: bool = False