this is exactly what we're doing in the fused classifier kernel, and this is an *algorithmic* improvement on top of today's torch compile, which doesn't do this
TOOLS
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Building the Fastest and Most Efficient Fine-Tuning Stack
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What does it take to build the #fastest, most #efficient fine-tuning stack? We got answers! Join our deep dive to learn: Latest fine-tuning #optimization techniques Metric driven analysis of each optimization How to get started on your own https://
pbase.ai/3Wq2ATG -
SQLite-utils tool for extracting strings into lookup tables
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I wrote a tool for pulling strings like that out into a lookup table https://
sqlite-utils.datasette.io/en/stable/cli.
html#cli-extract
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AI Agents: Rapid Creation and Deployment in Minutes
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AI Agents will be very common and AI will build these agents. We can help AI build these agents. First we get the AI to create a first draft, review it, then quickly deploy it in production. All of this can be done as quickly as 5 min for simpler agents, while complex agents
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New AI Product Would Dominate Humane and Rabbit Competition
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I mean something like that would instantly wipe the floor with all of these AI assistant companies e.g. Humane / Rabbit wouldn't it
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LangChain Weekly Release: LangSmith Improvements and LangGraph Tutorials
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LangChain Release Notes, Week of 4/29 Improved regression testing experience in LangSmith Hotkeys and mustache support in LangSmith New Evaluations content Three new video tutorials using LangGraph Community created content! Read it all here:
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Build RAG System Llama 3B-Instruct PDFs FAISS
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Build a RAG system with Llama 3B-Instruct for your PDFs Uses API for partitioning & chunking, FAISS for vector store, huggingface for the model It's a collab notebook so it's easy to get started! Thanks @mariaKhalusova for a great resource! https://
colab.research.google.com/drive/1BJYYyrP
Ve0_9EGyXqeNyzmVZDrCRZwsg?usp=sharing#scrollTo=Y2m2l-vt_RSp
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Hierarchical 3D Gaussians: Research and Videos Available
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Full research, more videos: https://
repo-sam.inria.fr/fungraph/hiera
rchical-3d-gaussians/
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Fine-tuning LLMs with RAG for personalized email generation
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Thanks, that's a great example "Panza produces a fine-tuned LLM that matches your writing style, pairing it with a Retrieval-Augmented Generation (RAG) component which helps it produce relevant emails." So fine-tuning for writing style, RAG for knowledge