mirror of
https://github.com/nomic-ai/gpt4all.git
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134 lines
4.9 KiB
Markdown
134 lines
4.9 KiB
Markdown
<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">
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<a href="https://gpt4all.io">GPT4All Website</a>
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</p>
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<p align="center">
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<a href="https://discord.gg/mGZE39AS3e">Discord</a>
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</p>
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<p align="center">
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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>
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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>
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<p align="center">
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<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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<p align="center">
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<a href="https://github.com/nomic-ai/pyllamacpp">:snake: Official Python Bindings</a>
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</p>
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<p align="center">
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<a href="https://github.com/nomic-ai/gpt4all-ts">:computer: Official Typescript Bindings</a>
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</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>
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<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>
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<p align="center">
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GPT4All is made possible by our compute partner <a href="https://www.paperspace.com/">Paperspace</a>.
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</p>
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## GPT4All: An ecosystem of open-source on-edge large language models.
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Run on an M1 Mac (not sped up!)
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### Chat Client
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Run any GPT4All model natively on your home desktop with the auto-updating desktop chat client. See website for exaustive list of models.
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<p align="center">
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<a href="https://gpt4all.io">GPT4All Website</a>
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</p>
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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)
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- [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.
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- `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
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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.
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For example, to load the `v1.2-jazzy` model and dataset, run:
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```python
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from datasets import load_dataset
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from transformers import AutoModelForCausalLM
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dataset = load_dataset("nomic-ai/gpt4all-j-prompt-generations", revision="v1.2-jazzy")
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model = AutoModelForCausalLM.from_pretrained("nomic-ai/gpt4all-j-prompt-generations", revision="v1.2-jazzy")
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```
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### GPT4All-J Training Instructions
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```bash
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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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```
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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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```
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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},
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year = {2023},
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publisher = {GitHub},
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journal = {GitHub repository},
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howpublished = {\url{https://github.com/nomic-ai/gpt4all}},
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}
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```
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