How Will AI Change Search And Content Creation?
#AI #AIio #BigData #ML #NLU #Futureofwork @gp_pulipaka @stratorob @PetiotEric @EvanKirstel @Fgraillot @HaroldSinnott @HeinzVHoenen @helene_wpli http://
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LLMS
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How AI Will Transform Search and Content Creation
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Map Rerank Chain: LLM Document Scoring and Ranking
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Map Rerank Finally, the Map Rerank Chain calls an LLM on each document, asking not only for an answer but also a score It then sorts the responses by the score and returns the highest one Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html#langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain
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Refine Documents Chain: Iterative Document Processing with LangChain
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Refine Documents Chain This chain uses the first document to get an initial response It then loops over the remaining docs, making a call to the language model to combining the response with the next document Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.refine.RefineDocumentsChain.html#langchain.chains.combine_documents.refine.RefineDocumentsChain
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MapReduceDocumentsChain: Processing Documents with LLM
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Map Reduce Chain This builds on top of the ReduceDocumentsChain It takes an LLMChain and a ReduceDocumentsChain. It first applies the LLMChain to each document, and then passes all the results to the ReduceDocumentsChain Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html#langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain
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StuffDocumentsChain: Basic Document Combination for LLMs
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Stuff Documents Chain The most basic CombineDocumentsChain, this takes N documents, formats them into a string using a PromptTemplate and `format_document`, and then combines them into a single prompt and passes them to an LLM Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html#langchain.chains.combine_documents.stuff.StuffDocumentsChain
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ReduceDocumentsChain: Combining Multiple Documents in LLM Prompts
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ReduceDocumentsChain But what if you have too many documents to fit into a single a prompt? That's where ReduceDocumentsChain comes into play It recursively combines documents together Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.reduce.ReduceDocumentsChain.html#langchain.chains.combine_documents.reduce.ReduceDocumentsChain
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Combining Documents with LLMs: LangChain Documentation Improvements
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Documents x LLMs Combining documents with LLMs is a key part of retrieval and chaining We've improved our @langchain reference documentation across the 5 major CombineDocumentsChains and helper functions to help with clarity and understanding of how these work
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Control Document Metadata in LLM Prompts with format_document
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`format_document` Want to control which metadata keys show up in the prompt? This helper function is rarely exposed, but is key to combining documents with LLMs It takes a Document and formats it into a string using a PromptTemplate Docs: https://
api.python.langchain.com/en/latest/sche
ma/langchain.schema.prompt_template.format_document.html#langchain.schema.prompt_template.format_document
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Appreciation for MPT Article and FSDP Implementation Question
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Thanks for writing & sharing your latest article on MPT. Really well written and has just the right level of detail .
One question though. You wrote > "The entire training framework is based upon PyTorch’s Fully Sharded Data Parallel (FSDP) package and uses no pipeline or -
OpenFlamingo v2: Advanced Multimodal Models Released
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Research blog post: OpenFlamingo v2: Next-level models and enhanced training setup! The paper by @anas_awadalla and @irena_gao
, with compute support from Stability AI, details five trained OpenFlamingo models across the 3B, 4B, and 9B scales. #StabilityAI Read more: