Hugging Face sentence-transformers is a Python framework for state-of-the-art sentence, text and image embeddings. You can use these embedding models from the HuggingFaceEmbeddings class.
Running sentence-transformers locally can be affected by your operating system and other global factors. It is recommended for experienced users only.

​
Setup

You’ll need to install the langchain_huggingface package as a dependency: 
%pip install -qU langchain-huggingface

​
Usage

from langchain_huggingface import HuggingFaceEmbeddings

embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")

text = "This is a test document."
query_result = embeddings.embed_query(text)

# show only the first 100 characters of the stringified vector
print(str(query_result)[:100] + "...")

[-0.038338568061590195, 0.12346471101045609, -0.028642969205975533, 0.05365273356437683, 0.008845377...

doc_result = embeddings.embed_documents([text, "This is not a test document."])
print(str(doc_result)[:100] + "...")

[[-0.038338497281074524, 0.12346471846103668, -0.028642890974879265, 0.05365274101495743, 0.00884535...

​
Troubleshooting

If you are having issues with the accelerate package not being found or failing to import, installing/upgrading it may help: 
%pip install -qU accelerate