mirror of
https://github.com/nomic-ai/gpt4all
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| .. | ||
| cmake | ||
| icons | ||
| qml | ||
| build_and_run.md | ||
| chat.cpp | ||
| chat.h | ||
| chatgpt.cpp | ||
| chatgpt.h | ||
| chatlistmodel.cpp | ||
| chatlistmodel.h | ||
| chatllm.cpp | ||
| chatllm.h | ||
| chatmodel.h | ||
| CMakeLists.txt | ||
| database.cpp | ||
| database.h | ||
| download.cpp | ||
| download.h | ||
| LICENSE | ||
| llm.cpp | ||
| llm.h | ||
| localdocs.cpp | ||
| localdocs.h | ||
| localdocsdb.h | ||
| localdocsmodel.cpp | ||
| localdocsmodel.h | ||
| logger.cpp | ||
| logger.h | ||
| main.cpp | ||
| main.qml | ||
| network.cpp | ||
| network.h | ||
| README.md | ||
| server.cpp | ||
| server.h | ||
| sysinfo.h | ||
| test_hw.cpp | ||
gpt4all-chat
Cross platform Qt based GUI for GPT4All versions with GPT-J as the base model. NOTE: The model seen in the screenshot is actually a preview of a new training run for GPT4All based on GPT-J. The GPT4All project is busy at work getting ready to release this model including installers for all three major OS's. In the meantime, you can try this UI out with the original GPT-J model by following build instructions below.
Install
One click installers for macOS, Linux, and Windows at https://gpt4all.io
Features
- Cross-platform (Linux, Windows, MacOSX)
- Fast CPU based inference using ggml for GPT-J based models
- The UI is made to look and feel like you've come to expect from a chatty gpt
- Check for updates so you can always stay fresh with latest models
- Easy to install with precompiled binaries available for all three major desktop platforms
- Multi-modal - Ability to load more than one model and switch between them
- Supports both llama.cpp and gptj.cpp style models
- Model downloader in GUI featuring many popular open source models
- Settings dialog to change temp, top_p, top_k, threads, etc
- Copy your conversation to clipboard
- Check for updates to get the very latest GUI
Feature wishlist
- Multi-chat - a list of current and past chats and the ability to save/delete/export and switch between
- Text to speech - have the AI response with voice
- Speech to text - give the prompt with your voice
- Python bindings
- Typescript bindings
- Plugin support for langchain other developer tools
- Save your prompt/responses to disk
- Upload prompt/response manually/automatically to nomic.ai to aid future training runs
- Syntax highlighting support for programming languages, etc.
- REST API with a built-in webserver in the chat gui itself with a headless operation mode as well
- Advanced settings for changing temperature, topk, etc. (DONE)
- YOUR IDEA HERE
Building and running
- Follow the visual instructions on the build_and_run page
Getting the latest
If you've already checked out the source code and/or built the program make sure when you do a git fetch to get the latest changes and that you also do git submodule update --init --recursive to update the submodules.
Manual download of models
- https://gpt4all.io/models/ggml-mpt-7b-chat.bin (default) (md5sum 756249d3d6abe23bde3b1ae272628640) Current best non-commercially licensable chat model based on MPT and trained by Mosaic ML.
- https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin (default) (md5sum 81a09a0ddf89690372fc296ff7f625af) Current best commercially licensable model based on GPT-J and trained by Nomic AI on the latest curated GPT4All dataset.
- https://gpt4all.io/models/ggml-gpt4all-l13b-snoozy.bin (md5sum 91f886b68fbce697e9a3cd501951e455) Current best non-commercially licensable model based on Llama 13b and trained by Nomic AI on the latest curated GPT4All dataset.
- https://gpt4all.io/models/ggml-gpt4all-j-v1.2-jazzy.bin (md5sum 879344aaa9d62fdccbda0be7a09e7976) A commercially licensable model based on GPT-J and trained by Nomic AI on the v2 GPT4All dataset.
- https://gpt4all.io/models/ggml-gpt4all-j-v1.1-breezy.bin (md5sum 61d48a82cb188cceb14ebb8082bfec37) A commercially licensable model based on GPT-J and trained by Nomic AI on the v1 GPT4All dataset.
- https://gpt4all.io/models/ggml-gpt4all-j.bin (md5sum 5b5a3f9b858d33b29b52b89692415595) A commercially licensable model based on GPT-J and trained by Nomic AI on the v0 GPT4All dataset.
- https://gpt4all.io/models/ggml-vicuna-7b-1.1-q4_2.bin (md5sum 29119f8fa11712704c6b22ac5ab792ea) An non-commercially licensable model based on Llama 7b and trained by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego.
- https://gpt4all.io/models/ggml-vicuna-13b-1.1-q4_2.bin (md5sum 95999b7b0699e2070af63bf5d34101a8) An non-commercially licensable model based on Llama 13b and trained by teams from UC Berkeley, CMU, Stanford, MBZUAI, and UC San Diego.
- https://gpt4all.io/models/ggml-wizardLM-7B.q4_2.bin (md5sum 99e6d129745a3f1fb1121abed747b05a) An non-commercially licensable model based on Llama 7b and trained by Microsoft and Peking University.
- https://gpt4all.io/models/ggml-stable-vicuna-13B.q4_2.bin (md5sum 6cb4ee297537c9133bddab9692879de0) An non-commercially licensable model based on Llama 13b and RLHF trained by Stable AI.
- https://gpt4all.io/models/ggml-mpt-7b-base.bin (md5sum 120c32a51d020066288df045ef5d52b9) A commercially licensable model base pre-trained by Mosaic ML.
- https://gpt4all.io/models/ggml-nous-gpt4-vicuna-13b.bin (md5sum d5eafd5b0bd0d615cfd5fd763f642dfe) A non-commercially licensable model based on Vicuna 13b, fine-tuned on ~180,000 instructions, trained by Nous Research.
- https://gpt4all.io/models/ggml-mpt-7b-instruct.bin (md5sum 1cfa4958f489f0a0d1ffdf6b37322809) A commercially licensable instruct model based on MPT and trained by Mosaic ML.
Terminal Only Interface with no Qt dependency
Check out https://github.com/kuvaus/LlamaGPTJ-chat which is using the llmodel backend so it is compliant with our ecosystem and all models downloaded above should work with it.
Contributing
- Pull requests welcome. See the feature wish list for ideas :)
License
The source code of this chat interface is currently under a MIT license. The underlying GPT4All-j model is released under non-restrictive open-source Apache 2 License.
The GPT4All-J license allows for users to use generated outputs as they see fit. Users take responsibility for ensuring their content meets applicable requirements for publication in a given context or region.