bartowski/neuralchat_v3_3_laser-exl2

Exllama v2 Quantizations of neuralchat_v3_3_laser

Using turboderp's ExLlamaV2 v0.0.11 for quantization.

The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)

Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.

Conversion was done using the default 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/cognitivecomputations/neuralchat_v3_3_laser

8.0 bits per weight

6.5 bits per weight

5.0 bits per weight

4.0 bits per weight

3.5 bits per weight

Download instructions

With git:

git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/neuralchat_v3_3_laser-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 neuralchat_v3_3_laser-exl2:

mkdir neuralchat_v3_3_laser-exl2
huggingface-cli download bartowski/neuralchat_v3_3_laser-exl2 --local-dir neuralchat_v3_3_laser-exl2 --local-dir-use-symlinks False

To download from a different branch, add the --revision parameter:

mkdir neuralchat_v3_3_laser-exl2
huggingface-cli download bartowski/neuralchat_v3_3_laser-exl2 --revision 4_0 --local-dir neuralchat_v3_3_laser-exl2 --local-dir-use-symlinks False