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

GPT4All Website

Discord

📗 Technical Report 3: GPT4All Snoozy and Groovy

📗 Technical Report 2: GPT4All-J

📗 Technical Report 1: GPT4All

🐍 Official Python Bindings

💻 Official Typescript Bindings

💬 Official Chat Interface

💬 Official Web Chat Interface

🦜️🔗 Official Langchain Backend

GPT4All is made possible by our compute partner Paperspace.

Run on an M1 Mac (not sped up!)

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

Windows

Ubuntu

If you have older hardware that only supports avx and not avx2 you can use these.

Mac/OSX - avx-only

Windows - avx-only

Ubuntu - avx-only

Find the most up-to-date information on the GPT4All Website

Please see GPT4All-J Technical Report for details.

• We are releasing the curated training data for anyone to replicate GPT4All-J here: GPT4All-J Training Data
  • Atlas Map of Prompts
  • Atlas Map of Responses

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 and data versions can be specified by passing a revision argument.

For example, to load the v1.2-jazzy model and dataset, run:

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")

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

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}},
}