emozilla/yarn-train-tokenized-16k-mistral
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How to use bartowski/Yarn-Mistral-7b-128k-exl2 with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/Yarn-Mistral-7b-128k-exl2", dtype="auto")Using turboderp's ExLlamaV2 v0.0.7 for quantization.
Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
Conversion was done using wikitext-103-raw-v1-test.parquet as calibration dataset.
Original model: https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k
With git:
git clone --single-branch --branch 4.0 https://huggingface.co/bartowski/Yarn-Mistral-7b-128k-exl2
With huggingface hub (credit to TheBloke for instructions):
pip3 install huggingface-hub
To download the main (only useful if you only care about measurement.json) branch to a folder called Yarn-Mistral-7b-128k-exl2:
mkdir Yarn-Mistral-7b-128k-exl2
huggingface-cli download bartowski/Yarn-Mistral-7b-128k-exl2 --local-dir Yarn-Mistral-7b-128k-exl2 --local-dir-use-symlinks False
To download from a different branch, add the --revision parameter:
mkdir Yarn-Mistral-7b-128k-exl2
huggingface-cli download bartowski/Yarn-Mistral-7b-128k-exl2 --revision 4.0 --local-dir Yarn-Mistral-7b-128k-exl2 --local-dir-use-symlinks False