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CharlesCNorton ce4dc2e789
typo in training log documentation (#2452) 
Corrected a typo in the training log documentation where "seemded" was changed to "seemed". This enhances the readability and professionalism of the document.

Signed-off-by: CharlesCNorton <135471798+CharlesCNorton@users.noreply.github.com>
2024-07-09 11:19:04 -04:00
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configs fix: update train scripts and configs for other models (#1164) 2023-07-12 15:18:24 -04:00
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build_map.py make scripts executable (#1555) 2023-10-24 09:28:21 -04:00
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data.py fix: update train scripts and configs for other models (#1164) 2023-07-12 15:18:24 -04:00
env.yaml mono repo structure 2023-05-01 15:45:23 -04:00
eval_figures.py make scripts executable (#1555) 2023-10-24 09:28:21 -04:00
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old-README.md llamamodel: fix BERT tokenization after llama.cpp update (#2381) 2024-05-28 13:11:57 -04:00
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requirements.txt fix: update train scripts and configs for other models (#1164) 2023-07-12 15:18:24 -04:00
train.py make scripts executable (#1555) 2023-10-24 09:28:21 -04:00
TRAINING_LOG.md typo in training log documentation (#2452) 2024-07-09 11:19:04 -04:00

README.md

Training GPT4All-J

Technical Reports

📗 Technical Report 3: GPT4All Snoozy and Groovy

📗 Technical Report 2: GPT4All-J

📗 Technical Report 1: GPT4All

GPT4All-J Training Data

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 and data versions can be specified by passing a revision argument.

For example, to load the v1.2-jazzy model and dataset, run:

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", revision="v1.2-jazzy")

GPT4All-J Training Instructions

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