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To use a fine-tuned model in a Sub Question Query Engine, you would first need to load the model from the Hugging Face repository. However, the provided extracts do not contain specific information on how to load a model from the Hugging Face repository and use it in a Sub Question Query Engine with LlamaIndex.
Once the model is loaded, you can use it to create a
ServiceContext and then use this context to create a
SubQuestionQueryEngine. Here is a general example of how you might do this, based on the information in the extracts:
from llama_index import ServiceContext, SubQuestionQueryEngine
# Assuming `model` is your loaded model
service_context = ServiceContext.from_defaults(llm=model)
# Assuming `vector_index` is your VectorStoreIndex
query_engine = vector_index.as_query_engine(service_context=service_context)
Please note that this is a general example and might need to be adjusted based on your specific use case and the actual way to load the model from the Hugging Face repository.
For more detailed instructions, you should refer to the
LlamaIndex documentation () or the
LlamaIndex examples on GitHub ().
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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