What I’m reading today. How Unstructured and LlamaIndex can help bring the power of LLM’s to your own data All You Need to Know to Build Your First LLM App — A Step-by-Step Tutorial to Document Loaders, Embeddings, Vector Stores… Continue Reading →
Large language models (LLM) are notoriously huge and expensive to work with. An LLM requires a lot of specialized hardware to train and manipulate. We’ve seen efforts to transform and quantize the models that result in smaller footprints and models… Continue Reading →
One can use this notebook to build a pipeline to parse and extract data from OCRed PDF files. Warning: When using LLMs for entity extraction, be sure to perform extensive quality control. They are very susceptible to distracting language (latching… Continue Reading →
LLMs promise to fundamentally change how we use AI across all industries. However, actually serving these models is challenging and can be surprisingly slow even on expensive hardware. Today we are excited to introduce vLLM, an open-source library for fast… Continue Reading →
Large language models are a powerful new primitive for building software. But since they are so new—and behave so differently from normal computing resources—it’s not always obvious how to use them.In this post, we’re sharing a reference architecture for the… Continue Reading →
This repository shares code used to implement the methods described in Unsupervised Machine Scoring of Free Response Answers—Validated Against Law School Final Exams, presented at the Computational Legal Studies Conference, March 2022, hosted by the Center for Computational Law at Singapore Management… Continue Reading →
Code 0n Github: https://github.com/FlowiseAI/Flowise Read the original story
Tutorial – train your own llama.cpp mini-ggml-model from scratch! by u/Evening_Ad6637 in LocalLLaMA Here I show how to train with llama.cpp your mini ggml model from scratch! these are currently very small models (20 mb when quantized) and I think… Continue Reading →
Developers can now fine-tune GPT-3 on their own data, creating a custom version tailored to their application. Customizing makes GPT-3 reliable for a wider variety of use cases and makes running the model cheaper and faster. You can use an existing… Continue Reading →
Second try. Probably need to be subscribed first, then post. Why just join a Mastodon instance if I can turn my entire blog in to a node in the federated social network space? This is the first post that attempts… Continue Reading →
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