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bartowski/
Yi-9B-200K-exl2

Name: Yi-9B-200K-exl2
Availability: InStock

text-generation

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Exllama v2 Quantizations of Yi-9B-200K

Using turboderp's ExLlamaV2 v0.0.15 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/01-ai/Yi-9B-200K

Download instructions

With git:

git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Yi-9B-200K-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 Yi-9B-200K-exl2:

shell

mkdir Yi-9B-200K-exl2
huggingface-cli download bartowski/Yi-9B-200K-exl2 --local-dir Yi-9B-200K-exl2 --local-dir-use-symlinks False

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

Linux:

shell

mkdir Yi-9B-200K-exl2-6_5
huggingface-cli download bartowski/Yi-9B-200K-exl2 --revision 6_5 --local-dir Yi-9B-200K-exl2-6_5 --local-dir-use-symlinks False

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

shell

mkdir Yi-9B-200K-exl2-6.5
huggingface-cli download bartowski/Yi-9B-200K-exl2 --revision 6_5 --local-dir Yi-9B-200K-exl2-6.5 --local-dir-use-symlinks False