gpt4all/README.md

<h1 align="center">GPT4All</h1>
<p align="center">Demo, data, and code to train open-source assistant-style large language model based on GPT-J and LLaMa</p>

<p align="center">
<a href="https://gpt4all.io">GPT4All Website</a>
</p>

<p align="center">
<a href="https://discord.gg/mGZE39AS3e">Discord</a>
</p>


<p align="center">
<a href="https://gpt4all.io/reports/GPT4All_Technical_Report_3.pdf">:green_book: Technical Report 3: GPT4All Snoozy and Groovy </a>
</p>

<p align="center">
<a href="https://static.nomic.ai/gpt4all/2023_GPT4All-J_Technical_Report_2.pdf">:green_book: Technical Report 2: GPT4All-J </a>
</p>

<p align="center">
<a href="https://s3.amazonaws.com/static.nomic.ai/gpt4all/2023_GPT4All_Technical_Report.pdf">:green_book: Technical Report 1: GPT4All</a>
</p>

<p align="center">
<a href="https://github.com/nomic-ai/pyllamacpp">:snake: Official Python Bindings</a>
</p>

<p align="center">
<a href="https://github.com/nomic-ai/gpt4all-ts">:computer: Official Typescript Bindings</a>
</p>

<p align="center">
<a href="[https://github.com/nomic-ai/gpt4all-chat](https://github.com/nomic-ai/gpt4all/blob/main/gpt4all-chat/README.md)">:speech_balloon: Official Chat Interface</a>
</p>

<p align="center">
<a href="https://github.com/nomic-ai/gpt4all-ui">:speech_balloon: Official Web Chat Interface</a>
</p>

<p align="center">
<a href="https://python.langchain.com/en/latest/modules/models/llms/integrations/gpt4all.html">🦜️🔗 Official Langchain Backend</a> 
</p>




<p align="center">
GPT4All is made possible by our compute partner <a href="https://www.paperspace.com/">Paperspace</a>.
</p>



## 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.

<p align="center">
<a href="https://gpt4all.io">GPT4All Website</a>
</p>

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}},
}
```