m-a-p/CodeFeedback-Filtered-Instruction
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Using turboderp's ExLlamaV2 v0.0.15 for quantization.
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-starcoder2-7b
| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
|---|---|---|---|---|---|---|
| 8_0 | 8.0 | 8.0 | 8.4 GB | 9.2 GB | 10.2 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| 6_5 | 6.5 | 8.0 | 7.1 GB | 7.9 GB | 8.9 GB | Very similar to 8.0, good tradeoff of size vs performance, recommended. |
| 5_0 | 5.0 | 6.0 | 5.8 GB | 6.6 GB | 7.6 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
| 4_25 | 4.25 | 6.0 | 5.1 GB | 5.9 GB | 6.9 GB | GPTQ equivalent bits per weight, slightly higher quality. |
| 3_5 | 3.5 | 6.0 | 4.5 GB | 5.3 GB | 6.3 GB | Lower quality, only use if you have to. |
With git:
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/dolphincoder-starcoder2-7b-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-starcoder2-7b-exl2:
mkdir dolphincoder-starcoder2-7b-exl2
huggingface-cli download bartowski/dolphincoder-starcoder2-7b-exl2 --local-dir dolphincoder-starcoder2-7b-exl2 --local-dir-use-symlinks False
To download from a different branch, add the --revision parameter:
Linux:
mkdir dolphincoder-starcoder2-7b-exl2-6_5
huggingface-cli download bartowski/dolphincoder-starcoder2-7b-exl2 --revision 6_5 --local-dir dolphincoder-starcoder2-7b-exl2-6_5 --local-dir-use-symlinks False
Windows (which apparently doesn't like _ in folders sometimes?):
mkdir dolphincoder-starcoder2-7b-exl2-6.5
huggingface-cli download bartowski/dolphincoder-starcoder2-7b-exl2 --revision 6_5 --local-dir dolphincoder-starcoder2-7b-exl2-6.5 --local-dir-use-symlinks False