Part 6/7:
With Lang Chain, you can create chains that link several models together, allowing for sophisticated operations like summarization, refinement, and question answering.
summary = my_summarization_chain(text)
response = my_qa_pipeline(question, context=summary)
Utilizing such chaining enables you to build applications that are not only reactive but intelligent.
Conclusion
The outlined steps in this guide demonstrate how to harness the power of open-source machine learning models from Hugging Face on your local system. By utilizing Python's versatile toolset through Transformers and Lang Chain, you can easily implement advanced functionalities without incurring costs.