mlx-whatsapp

This is an experimental project to convert your chat backups from Whatsapp to finetune mistral using mlx. The lora.py, models.py and convert.py are from https://github.com/ml-explore/mlx-examples

How to backup your chats

Go to whatsapp -> Settings -> Export Chat -> Select group conversation -> Without Media

Download Mistral and convert to quantized version

Install the dependencies:

pip install -r requirements.txt

Next, download and convert the model. The Mistral weights can be downloaded with:

curl -O https://files.mistral-7b-v0-1.mistral.ai/mistral-7B-v0.1.tar
tar -xf mistral-7B-v0.1.tar

Convert the model with:

python convert.py \
    --torch-path mistral-7B-v0.1 \
    --mlx-path mistral_mlx_q -q

Converting the files

Save your file exported from whatsapp as chat.txt. Then create the training files below

python whatsapp.py --input_file chat.txt --output_file chat.jsonl --test_file data/test.jsonl --train_file data/train.jsonl --valid_file data/valid.jsonl

By default the test and validation files take 30 samples. You can adjust them.

Training

 python lora.py --model mistral_mlx_q --train --iters 600 --data ./data --batch-size 2 --adapter-file whatsapp.npz

Inference