gpt4all

nomic-ai / gpt4all

GPT4All 是一个可在任何设备上本地运行大语言模型的开源工具,支持商用,帮助开发者轻松部署离线 LLM 应用。

C++ LLM 应用 AI 基础设施 桌面/移动应用 本地大模型 离线推理 跨平台 开源商用

为什么值得看

编辑点评

它解决了云端 API 的隐私和成本问题,让大模型能在普通电脑甚至移动设备上运行。采用 C++ 实现,性能好,支持多种量化格式和丰富的模型库。适合需要离线推理、数据敏感或边缘部署的场景。注意:本地模型能力相比云端大模型有差距,需在效果和资源之间权衡。

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同类项目

同场景 · LLM 应用 / AI 基础设施 / 桌面/移动应用

项目文档

来自 GitHub README · main 分支

GPT4All

Now with support for DeepSeek R1 Distillations

WebsiteDocumentationDiscordYouTube Tutorial

GPT4All runs large language models (LLMs) privately on everyday desktops & laptops.

No API calls or GPUs required - you can just download the application and get started.

Read about what's new in our blog.

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https://github.com/nomic-ai/gpt4all/assets/70534565/513a0f15-4964-4109-89e4-4f9a9011f311

GPT4All is made possible by our compute partner Paperspace.

Windows Installer

Windows ARM Installer

macOS Installer

Ubuntu Installer

The Windows and Linux builds require Intel Core i3 2nd Gen / AMD Bulldozer, or better.

The Windows ARM build supports Qualcomm Snapdragon and Microsoft SQ1/SQ2 processors.

The Linux build is x86-64 only (no ARM).

The macOS build requires Monterey 12.6 or newer. Best results with Apple Silicon M-series processors.

See the full System Requirements for more details.

Flathub (community maintained)

Install GPT4All Python

gpt4all gives you access to LLMs with our Python client around llama.cpp implementations.

Nomic contributes to open source software like llama.cpp to make LLMs accessible and efficient for all.

pip install gpt4all
from gpt4all import GPT4All
model = GPT4All("Meta-Llama-3-8B-Instruct.Q4_0.gguf") # downloads / loads a 4.66GB LLM
with model.chat_session():
    print(model.generate("How can I run LLMs efficiently on my laptop?", max_tokens=1024))

Integrations

:parrot::link: Langchain :card_file_box: Weaviate Vector Database - module docs :telescope: OpenLIT (OTel-native Monitoring) - Docs

Release History

  • July 2nd, 2024: V3.0.0 Release
    • Fresh redesign of the chat application UI
    • Improved user workflow for LocalDocs
    • Expanded access to more model architectures
  • October 19th, 2023: GGUF Support Launches with Support for:
    • Mistral 7b base model, an updated model gallery on our website, several new local code models including Rift Coder v1.5
    • Nomic Vulkan support for Q4_0 and Q4_1 quantizations in GGUF.
    • Offline build support for running old versions of the GPT4All Local LLM Chat Client.
  • September 18th, 2023: Nomic Vulkan launches supporting local LLM inference on NVIDIA and AMD GPUs.
  • July 2023: Stable support for LocalDocs, a feature that allows you to privately and locally chat with your data.
  • June 28th, 2023: Docker-based API server launches allowing inference of local LLMs from an OpenAI-compatible HTTP endpoint.

Contributing

GPT4All welcomes contributions, involvement, and discussion from the open source community! Please see CONTRIBUTING.md and follow the issues, bug reports, and PR markdown templates.

Check project discord, with project owners, or through existing issues/PRs to avoid duplicate work. Please make sure to tag all of the above with relevant project identifiers or your contribution could potentially get lost. Example tags: backend, bindings, python-bindings, documentation, etc.

Citation

If you utilize this repository, models or data in a downstream project, please consider citing it with:

@misc{gpt4all,
  author = {Yuvanesh Anand and Zach Nussbaum and Brandon Duderstadt and Benjamin Schmidt and Andriy Mulyar},
  title = {GPT4All: Training an Assistant-style Chatbot with Large Scale Data Distillation from GPT-3.5-Turbo},
  year = {2023},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/nomic-ai/gpt4all}},
}

文档抓取自 GitHub 仓库 README,版权归原作者所有;已过滤徽章等噪音并经安全消毒后展示。