Hugging face sentence embeddings on Dominolab Localy
goodafternoon.I am requesting  for assistance. I’m working on a program for querying documents  using Langchain and huggingFace  on DominoLab, but I’ve loaded the hugging face embedding on the Lab  and the huging face model.I was able to test the embedding model, and everything is working properlyHowever, since the embedding model is local, how do call then on the following code.load documentloader = PyPDFLoader(“INC.PC.001.ITG_Incident_Process_Sheet_EN 2022-07-29 (2).pdf”)documents = loader.load()split the documents into chunkstext_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)texts = text_splitter.split_documents(documents)select which embeddings we want to use( my issue is the embedding model how to call this model)embeddings =sentence-transformers/all-mpnet-base-v2create the vectorestore to use as the indexdb = Chroma.from_documents(texts, embeddings)expose this index in a retriever interfaceretriever = db.as_retriever(search_type=“similarity”, search_kwargs={“k”:2})create a chain to answer questionsqa = RetrievalQA.from_chain_type(llm=local_llm, chain_type="refine", retriever=retriever, return_source_documents=True)query = “who is frederic Strauss?”result = qa({“query”: query})to test sentence embedding model i usedfrom codeWhatsApp Image 2023-04-28 at 2.55.49 PM1600×1200 243 KB