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https://github.com/nomic-ai/gpt4all

GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.
https://github.com/nomic-ai/gpt4all

ai-chat llm-inference

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GPT4All: Run Local LLMs on Any Device. Open-source and available for commercial use.

Awesome Lists containing this project

README 

          
GPT4All





  Now with support for DeepSeek R1 Distillations






  Website • Documentation • Discord • YouTube 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.





  Subscribe to the newsletter




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





GPT4All is made possible by our compute partner Paperspace.




## Download Links





  — 

     Windows Installer

   —





  — 

     Windows ARM Installer

   —





  — 

     macOS Installer

   —





  — 

     Ubuntu Installer

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  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](gpt4all-chat/system_requirements.md) for more details.











  

    Get it on Flathub


    Flathub (community maintained)

  




## Install GPT4All Python



`gpt4all` gives you access to LLMs with our Python client around [`llama.cpp`](https://github.com/ggerganov/llama.cpp) implementations. 



Nomic contributes to open source software like [`llama.cpp`](https://github.com/ggerganov/llama.cpp) to make LLMs accessible and efficient **for all**.



```bash

pip install gpt4all

```



```python

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](https://python.langchain.com/v0.2/docs/integrations/providers/gpt4all/)

:card_file_box: [Weaviate Vector Database](https://github.com/weaviate/weaviate) - [module docs](https://weaviate.io/developers/weaviate/modules/retriever-vectorizer-modules/text2vec-gpt4all)

:telescope: [OpenLIT (OTel-native Monitoring)](https://github.com/openlit/openlit) - [Docs](https://docs.openlit.io/latest/integrations/gpt4all)



## 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](https://blog.nomic.ai/posts/gpt4all-gpu-inference-with-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](https://blog.nomic.ai/posts/gpt4all-gpu-inference-with-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.



[Docker-based API server]: https://github.com/nomic-ai/gpt4all/tree/cef74c2be20f5b697055d5b8b506861c7b997fab/gpt4all-api



## 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}},

}

```