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Exllama v2 Quantizations of dolphincoder-starcoder2-15b

Using turboderp's ExLlamaV2 v0.0.15 preview 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.

Original model: https://huggingface.co/cognitivecomputations/dolphincoder-starcoder2-15b

Branch Bits lm_head bits VRAM (4k) VRAM (16k) VRAM (32k) Description
8_0 8.0 8.0 16.6 GB 17.5 GB 18.8 GB Maximum quality that ExLlamaV2 can produce, near unquantized performance.
6_5 6.5 8.0 13.9 GB 14.9 GB 16.2 GB Near unquantized performance at vastly reduced size, recommended.
5_0 5.0 6.0 11.2 GB 12.2 GB 13.5 GB Slightly lower quality vs 6.5.
4_25 4.25 6.0 9.8 GB 10.7 GB 12.0 GB GPTQ equivalent bits per weight.
3_5 3.5 6.0 8.4 GB 9.3 GB 10.6 GB Lower quality, not recommended.

Download instructions

With git:

git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/dolphincoder-starcoder2-15b-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 dolphincoder-starcoder2-15b-exl2:

mkdir dolphincoder-starcoder2-15b-exl2
huggingface-cli download bartowski/dolphincoder-starcoder2-15b-exl2 --local-dir dolphincoder-starcoder2-15b-exl2 --local-dir-use-symlinks False

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

Linux:

mkdir dolphincoder-starcoder2-15b-exl2-6_5
huggingface-cli download bartowski/dolphincoder-starcoder2-15b-exl2 --revision 6_5 --local-dir dolphincoder-starcoder2-15b-exl2-6_5 --local-dir-use-symlinks False

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

mkdir dolphincoder-starcoder2-15b-exl2-6.5
huggingface-cli download bartowski/dolphincoder-starcoder2-15b-exl2 --revision 6_5 --local-dir dolphincoder-starcoder2-15b-exl2-6.5 --local-dir-use-symlinks False
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