adithya-s-k/LLM-InferenceNet

LLM InferenceNet is a C++ project designed to facilitate fast and efficient inference from Large Language Models (LLMs) using a client-server architecture. It enables optimized interactions with pre-trained language models, making deployment on edge devices easier.

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Experimental

This project helps developers integrate powerful Large Language Models (LLMs) like LLaMa2 into their applications, especially on resource-constrained 'edge' devices. It takes a pre-trained LLM and user input, then outputs text predictions or responses, optimizing the process for speed. Developers and engineers working on AI-powered applications, particularly for embedded systems or local processing, would use this.

No commits in the last 6 months.

Use this if you need to run large language models efficiently and quickly on edge devices or within a client-server architecture, minimizing computational load.

Not ideal if you are an end-user looking for a ready-to-use application, or if you don't have development expertise in C++ and deploying AI models.

edge-computing AI-application-development embedded-systems natural-language-processing-deployment server-side-AI
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 8 / 25
Community 0 / 25

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C++

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Last pushed

Jul 28, 2023

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