abhinand5/gptq_for_langchain

A guide about how to use GPTQ models with langchain

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This guide helps developers integrate private, quantized open-source language models (LLMs) like WizardLM into applications built with LangChain. It provides practical steps and examples for setting up these models to process text input and generate responses, ensuring data privacy by running on local hardware. The target users are developers who want to leverage powerful LLMs within their applications without relying on external APIs.

No commits in the last 6 months.

Use this if you are a developer looking to build applications with open-source LLMs using LangChain, where data privacy and local execution are critical.

Not ideal if you are a non-developer seeking an out-of-the-box application, or if you prefer using cloud-based LLM APIs.

AI-application-development privacy-preserving-AI natural-language-processing LLM-deployment local-AI-development
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 17 / 25

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40

Forks

11

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Aug 19, 2023

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