It doesn't get much attention these days (in both senses) but a new version of @scikit_learn
, my favorite machine learning library, is out! – PyTorch support for LinearDiscriminant Analysis
– Validation Curves
– Decision tree with N/A features
– and more
AI
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New scikit-learn Version Released with PyTorch Support and Features
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GPT-Migrate: Migrate Your Codebase Between Frameworks
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◐ GPT-Migrate ◑
— AK (@_akhaliq) 5 juillet 2023
migrate your codebase from one framework or language to another
github: https://t.co/FkMdhzW2Kj pic.twitter.com/JWZW19TtNv◐ GPT-Migrate ◑ migrate your codebase from one framework or language to another github: https://
github.com/0xpayne/gpt-mi
grate
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Microsoft Azure AI Studio Enables Custom Copilot Development
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How Microsoft's Azure AI Studio Will Allow Companies To Build Custom Copilots – SlashGear Microsoft Azure AI Studio, as the company announced at Build 2023, is a new endeavor that will allow users to further the burgeoning potential of AI. Read More: https://
bit.ly/3XydQfn -
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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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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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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