Exllama v2 Quantizations of juanako-7b-UNA
Using turboderp's ExLlamaV2 v0.0.10 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.
Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
Original model: https://huggingface.co/fblgit/juanako-7b-UNA
Download instructions
With git:
git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/juanako-7b-UNA-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 juanako-7b-UNA-exl2
:
mkdir juanako-7b-UNA-exl2
huggingface-cli download bartowski/juanako-7b-UNA-exl2 --local-dir juanako-7b-UNA-exl2 --local-dir-use-symlinks False
To download from a different branch, add the --revision
parameter:
mkdir juanako-7b-UNA-exl2
huggingface-cli download bartowski/juanako-7b-UNA-exl2 --revision 4_0 --local-dir juanako-7b-UNA-exl2 --local-dir-use-symlinks False
Dataset used to train bartowski/juanako-7b-UNA-exl2
Evaluation results
- accuracy on truthful_qavalidation set self-reported65.130
- accuracy on ai2_arctest set self-reported68.170
- accuracy on Rowan/hellaswagtest set self-reported85.340
- accuracy on winograndetest set self-reported78.850
- accuracy on cais/mmlutest set self-reported62.470
- accuracy on piqatest set self-reported83.570
- accuracy on dropvalidation set self-reported38.740
- accuracy on bigbio/pubmed_qavalidation set self-reported76.000