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# gpt4all | ||
<h1 align="center">GPT4All</h1> | ||
<p align="center">Demo, data and code to train an assistant-style large language model</p> | ||
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# Try it yourself | ||
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-- TODO LLAMA C++ code | ||
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# Setup | ||
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# Reproducibility | ||
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You can find trained LoRa model weights at: | ||
- gpt4all-lora https://huggingface.co/nomic-ai/gpt4all-lora | ||
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We are not distributing LLaMa 7B checkpoint they need to be used in association with. | ||
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To reproduce our LoRA training run, do the following: | ||
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## Setup | ||
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Clone the repo | ||
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`git clone --recurse-submodules [email protected]:nomic-ai/gpt4all.git` | ||
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`git submodule configure && git submodule update` | ||
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Setup the environment | ||
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``` | ||
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## Train | ||
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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.json train.py --config configs/train/finetune-7b.yaml` | ||
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If you utilize this reposistory, models or data in a downstream project, please consider citing it with: | ||
``` | ||
@misc{gpt4all, | ||
author = {Yuvanesh Anand and Zachary 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}}, | ||
} | ||
``` | ||
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