GPT4All

Demo, data, and code to train open-source assistant-style large language model based on GPT-J and LLaMa

GPT4All is made possible by our compute partner Paperspace.

## GPT4All: An ecosystem of open-source on-edge large language models. ![gpt4all-j-demo](https://user-images.githubusercontent.com/13879686/231876409-e3de1934-93bb-4b4b-9013-b491a969ebbc.gif) Run on an M1 Mac (not sped up!) ### Chat Client Run any GPT4All model natively on your home desktop with the auto-updating desktop chat client. See website for exaustive list of models.

GPT4All Website

Direct Installer Links: [Mac/OSX](https://gpt4all.io/installers/gpt4all-installer-darwin.dmg) [Windows](https://gpt4all.io/installers/gpt4all-installer-win64.exe) [Ubuntu](https://gpt4all.io/installers/gpt4all-installer-linux.run) If you have older hardware that only supports avx and not avx2 you can use these. [Mac/OSX - avx-only](https://gpt4all.io/installers/gpt4all-installer-darwin-avx-only.dmg) [Windows - avx-only](https://gpt4all.io/installers/gpt4all-installer-win64-avx-only.exe) [Ubuntu - avx-only](https://gpt4all.io/installers/gpt4all-installer-linux-avx-only.run) Find the most up-to-date information on the [GPT4All Website](https://gpt4all.io/) ## Training GPT4All-J Please see [GPT4All-J Technical Report](https://static.nomic.ai/gpt4all/2023_GPT4All-J_Technical_Report_2.pdf) for details. ### GPT4All-J Training Data - We are releasing the curated training data for anyone to replicate GPT4All-J here: [GPT4All-J Training Data](https://huggingface.co/datasets/nomic-ai/gpt4all-j-prompt-generations) - [Atlas Map of Prompts](https://atlas.nomic.ai/map/gpt4all-j-prompts-curated) - [Atlas Map of Responses](https://atlas.nomic.ai/map/gpt4all-j-response-curated) We have released updated versions of our `GPT4All-J` model and training data. - `v1.0`: The original model trained on the v1.0 dataset - `v1.1-breezy`: Trained on a filtered dataset where we removed all instances of AI language model - `v1.2-jazzy`: Trained on a filtered dataset where we also removed instances like I'm sorry, I can't answer... and AI language model The [models](https://huggingface.co/nomic-ai/gpt4all-j) and [data](https://huggingface.co/datasets/nomic-ai/gpt4all-j-prompt-generations) versions can be specified by passing a `revision` argument. For example, to load the `v1.2-jazzy` model and dataset, run: ```python from datasets import load_dataset from transformers import AutoModelForCausalLM dataset = load_dataset("nomic-ai/gpt4all-j-prompt-generations", revision="v1.2-jazzy") model = AutoModelForCausalLM.from_pretrained("nomic-ai/gpt4all-j-prompt-generations", revision="v1.2-jazzy") ``` ### GPT4All-J Training Instructions ```bash accelerate launch --dynamo_backend=inductor --num_processes=8 --num_machines=1 --machine_rank=0 --deepspeed_multinode_launcher standard --mixed_precision=bf16 --use_deepspeed --deepspeed_config_file=configs/deepspeed/ds_config_gptj.json train.py --config configs/train/finetune_gptj.yaml ``` ## 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}}, } ```