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I am using LLAMA-2 13 B model with langchain
For embeddings i am using
embeddings = HuggingFaceInstructEmbeddings(
model_name="WhereIsAI/UAE-Large-V1", model_kwargs={"device": DEVICE}
)
Issue with current documentation:
I am using LLAMA-2 13 B model with langchain
For embeddings i am using
embeddings = HuggingFaceInstructEmbeddings(
model_name="WhereIsAI/UAE-Large-V1", model_kwargs={"device": DEVICE}
)
db = FAISS.load_local(path, embeddings,allow_dangerous_deserialization=True)
prompt_template = f"{template}\nCONTEXT:\n\n{{context}}\nQuestion: {{question}}\n[INST]"
prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
result = qa_chain({"context": "", "query": user_input+" Just tell what you know"})
Chunk Size:
text_splitter = RecursiveCharacterTextSplitter(chunk_size=512, chunk_overlap=60)
texts = text_splitter.split_documents(docs)
For question/answers it's not providing correct retriever document and answers.
Kindly provide me answers how i need to fix this. it's high prority.
Idea or request for content:
No response
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