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< h1 align = "center" > GPT4All< / h1 >
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< p align = "center" > Demo, data, and code to train open-source assistant-style large language model based on GPT-J and LLaMa< / p >
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< p align = "center" >
< a href = "https://gpt4all.io" > GPT4All Website< / a >
< / p >
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< a href = "https://discord.gg/mGZE39AS3e" > Discord< / a >
< / p >
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< a href = "https://gpt4all.io/reports/GPT4All_Technical_Report_3.pdf" > :green_book: Technical Report 3: GPT4All Snoozy and Groovy < / a >
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< p align = "center" >
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< a href = "https://static.nomic.ai/gpt4all/2023_GPT4All-J_Technical_Report_2.pdf" > :green_book: Technical Report 2: GPT4All-J < / a >
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< / 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 >
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< / p >
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< a href = "https://github.com/nomic-ai/pyllamacpp" > :snake: Official Python Bindings< / a >
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< a href = "https://github.com/nomic-ai/gpt4all-ts" > :computer: Official Typescript Bindings< / a >
< / p >
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< p align = "center" >
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< a href = "https://github.com/nomic-ai/gpt4all/blob/main/gpt4all-chat/README.md" > :speech_balloon: Official Chat Interface< / a >
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< / p >
< p align = "center" >
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< a href = "https://github.com/nomic-ai/gpt4all-ui" > :speech_balloon: Official Web Chat Interface< / a >
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< / p >
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< p align = "center" >
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< a href = "https://python.langchain.com/en/latest/modules/models/llms/integrations/gpt4all.html" > 🦜️🔗 Official Langchain Backend< / a >
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< p align = "center" >
GPT4All is made possible by our compute partner < a href = "https://www.paperspace.com/" > Paperspace< / a > .
< / p >
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## GPT4All: An ecosystem of open-source on-edge large language models.
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![gpt4all-j-demo ](https://user-images.githubusercontent.com/13879686/231876409-e3de1934-93bb-4b4b-9013-b491a969ebbc.gif )
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Run on an M1 Mac (not sped up!)
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### 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:
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[Mac/OSX ](https://gpt4all.io/installers/gpt4all-installer-darwin.dmg )
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[Windows ](https://gpt4all.io/installers/gpt4all-installer-win64.exe )
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[Ubuntu ](https://gpt4all.io/installers/gpt4all-installer-linux.run )
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If you have older hardware that only supports avx and not avx2 you can use these.
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[Mac/OSX - avx-only ](https://gpt4all.io/installers/gpt4all-installer-darwin-avx-only.dmg )
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[Windows - avx-only ](https://gpt4all.io/installers/gpt4all-installer-win64-avx-only.exe )
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[Ubuntu - avx-only ](https://gpt4all.io/installers/gpt4all-installer-linux-avx-only.run )
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Find the most up-to-date information on the [GPT4All Website ](https://gpt4all.io/ )
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## Training GPT4All-J
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Please see [GPT4All-J Technical Report ](https://static.nomic.ai/gpt4all/2023_GPT4All-J_Technical_Report_2.pdf ) for details.
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### GPT4All-J Training Data
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- 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 )
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- [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 )
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We have released updated versions of our `GPT4All-J` model and training data.
- `v1.0` : The original model trained on the v1.0 dataset
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- `v1.1-breezy` : Trained on a filtered dataset where we removed all instances of AI language model
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- `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")
```
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### GPT4All-J Training Instructions
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```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
```
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## Citation
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If you utilize this repository, models or data in a downstream project, please consider citing it with:
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```
@misc {gpt4all,
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author = {Yuvanesh Anand and Zach Nussbaum and Brandon Duderstadt and Benjamin Schmidt and Andriy Mulyar},
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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}},
}
```