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bartowski/
Smegmma-Deluxe-9B-v1-exl2

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Exllama v2 Quantizations of Smegmma-Deluxe-9B-v1

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.

<bos><start_of_turn>user
{prompt}<end_of_turn>
<start_of_turn>model
<end_of_turn>
<start_of_turn>model

Note that this model does not support a System prompt.

Available sizes

Branch	Bits	lm_head bits	VRAM (4k)	VRAM (16k)	VRAM (32k)	Description
8_0	8.0	8.0	11.9 GB	15.9 GB	21.3 GB	Maximum quality that ExLlamaV2 can produce, near unquantized performance.
6_5	6.5	8.0	10.4 GB	14.4 GB	19.8 GB	Very similar to 8.0, good tradeoff of size vs performance, recommended.
5_0	5.0	6.0	8.6 GB	12.6 GB	18.0 GB	Slightly lower quality vs 6.5, but usable on 8GB cards.
4_25	4.25	6.0	7.9 GB	11.9 GB	17.3 GB	GPTQ equivalent bits per weight, slightly higher quality.
3_5	3.5	6.0	7.1 GB	11.1 GB	16.9 GB	Lower quality, only use if you have to.

With git:

git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Smegmma-Deluxe-9B-v1-exl2 Smegmma-Deluxe-9B-v1-exl2-6_5

With huggingface hub (credit to TheBloke for instructions):

pip3 install huggingface-hub

To download a specific branch, use the --revision parameter. For example, to download the 6.5 bpw branch:

Linux:

huggingface-cli download bartowski/Smegmma-Deluxe-9B-v1-exl2 --revision 6_5 --local-dir Smegmma-Deluxe-9B-v1-exl2-6_5

Windows (which apparently doesn't like _ in folders sometimes?):

huggingface-cli download bartowski/Smegmma-Deluxe-9B-v1-exl2 --revision 6_5 --local-dir Smegmma-Deluxe-9B-v1-exl2-6.5

Want to support my work? Visit my ko-fi page here: https://ko-fi.com/bartowski