docs: Update Features->Embeddings page to reflect backend restructuring (#1325)

* Update path to sentencetransformers backend for local execution

Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>

* Rename huggingface-embeddings -> sentencetransformers in embeddings.md for consistency with the backend structure

The Dockerfile still knows the "huggingface-embeddings"
backend (I assume for compatibility reasons) but uses the
sentencetransformers backend under the hood anyway.

I figured it would be good to update the docs to use the new naming to
make it less confusing moving forward. As the docker container knows
both the "huggingface-embeddings" and the "sentencetransformers"
backend, this should not break anything.

Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>

---------

Signed-off-by: Marcus Köhler <khler.marcus@gmail.com>

docs/content/features/embeddings.md

@@ -61,23 +61,23 @@ curl http://localhost:8080/embeddings -X POST -H "Content-Type: application/json
 
 ## Huggingface embeddings
 
-To use `sentence-formers` and models in `huggingface` you can use the `huggingface` embedding backend.
+To use `sentence-transformers` and models in `huggingface` you can use the `sentencetransformers` embedding backend.
 
 ```yaml
 name: text-embedding-ada-002
-backend: huggingface-embeddings
+backend: sentencetransformers
 embeddings: true
 parameters:
   model: all-MiniLM-L6-v2
 ```
 
-The `huggingface` backend uses Python [sentence-transformers](https://github.com/UKPLab/sentence-transformers). For a list of all pre-trained models available see here: https://github.com/UKPLab/sentence-transformers#pre-trained-models
+The `sentencetransformers` backend uses Python [sentence-transformers](https://github.com/UKPLab/sentence-transformers). For a list of all pre-trained models available see here: https://github.com/UKPLab/sentence-transformers#pre-trained-models
 
 {{% notice note %}}
 
-- The `huggingface` backend is an optional backend of LocalAI and uses Python. If you are running `LocalAI` from the containers you are good to go and should be already configured for use. If you are running `LocalAI` manually you must install the python dependencies (`pip install -r /path/to/LocalAI/extra/requirements`) and specify the extra backend in the `EXTERNAL_GRPC_BACKENDS` environment variable ( `EXTERNAL_GRPC_BACKENDS="huggingface-embeddings:/path/to/LocalAI/extra/grpc/huggingface/huggingface.py"` ) .
-- The `huggingface` backend does support only embeddings of text, and not of tokens. If you need to embed tokens you can use the `bert` backend or `llama.cpp`.
-- No models are required to be downloaded before using the `huggingface` backend. The models will be downloaded automatically the first time the API is used.
+- The `sentencetransformers` backend is an optional backend of LocalAI and uses Python. If you are running `LocalAI` from the containers you are good to go and should be already configured for use. If you are running `LocalAI` manually you must install the python dependencies (`pip install -r /path/to/LocalAI/extra/requirements`) and specify the extra backend in the `EXTERNAL_GRPC_BACKENDS` environment variable ( `EXTERNAL_GRPC_BACKENDS="sentencetransformers:/path/to/LocalAI/backend/python/sentencetransformers/sentencetransformers.py"` ) .
+- The `sentencetransformers` backend does support only embeddings of text, and not of tokens. If you need to embed tokens you can use the `bert` backend or `llama.cpp`.
+- No models are required to be downloaded before using the `sentencetransformers` backend. The models will be downloaded automatically the first time the API is used.
 
 {{% /notice %}}