AntonioGr7/pratical-llms
A collection of hand on notebook for LLMs practitioner
This is a collection of practical guides for working with Large Language Models (LLMs). It provides step-by-step instructions and code examples to help you optimize LLMs for performance and resource usage, evaluate their quality, and deploy them efficiently. The notebooks guide you through processes like model quantization, sharding, and inference, helping you transform large, resource-intensive models into more manageable and deployable assets. This is for LLM engineers and machine learning practitioners who build and deploy AI applications.
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Use this if you need hands-on guidance to optimize, evaluate, and deploy Large Language Models, especially when dealing with memory constraints or performance requirements.
Not ideal if you are looking for a theoretical overview of LLMs or a high-level API for general text generation without needing to manage model specifics.
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Jan 13, 2025
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