gpt4all/README.md

<h1 align="center">GPT4All</h1>
<p align="center">Open-source assistant-style large language models that run locally on CPU</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/gpt4all/tree/main/gpt4all-bindings/python/README.md">: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/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!)


## Contributing
GPT4All welcomes contribution, involvment, and discussion from the open source community!
Please see CONTRIBUTING.md and follow the issue, bug report, 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.
 


### 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/)

### Python Bindings

```bash
pip install gpt4all
```

```python
import gpt4all
gptj = gpt4all.GPT4All("ggml-gpt4all-j-v1.3-groovy")
messages = [{"role": "user", "content": "Name 3 colors"}]
gptj.chat_completion(messages)
```

## 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}},
}
```