argilla/distilabel-intel-orca-dpo-pairs
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Using turboderp's ExLlamaV2 v0.0.11 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/argilla/distilabeled-Hermes-2.5-Mistral-7B
Model Size: 7b
| Branch | Bits | lm_head bits | Dataset | Size | Description |
|---|---|---|---|---|---|
| 8_0 | 8.0 | 8.0 | Default | 9.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
| 6_5 | 6.5 | 8.0 | Default | 8.6 GB | Very similar to 8.0, good tradeoff of size vs performance, recommended. |
| 5_0 | 5.0 | 6.0 | Default | 7.4 GB | Slightly lower perplexity vs 6.5. |
| 4_0 | 4.0 | 6.0 | Default | 6.5 GB | Just under GPTQ equivalent bits per weight. |
| 3_5 | 3.5 | 6.0 | Default | 6.1 GB | Lower quality, only use if you have to. |
All VRAM requirements estimated from 16k context. For 32k context add ~2 GB.
With git:
git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/distilabeled-Hermes-2.5-Mistral-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 distilabeled-Hermes-2.5-Mistral-7B-exl2:
mkdir distilabeled-Hermes-2.5-Mistral-7B-exl2
huggingface-cli download bartowski/distilabeled-Hermes-2.5-Mistral-7B-exl2 --local-dir distilabeled-Hermes-2.5-Mistral-7B-exl2 --local-dir-use-symlinks False
To download from a different branch, add the --revision parameter:
mkdir distilabeled-Hermes-2.5-Mistral-7B-exl2-6_5
huggingface-cli download bartowski/distilabeled-Hermes-2.5-Mistral-7B-exl2 --revision 6_5 --local-dir distilabeled-Hermes-2.5-Mistral-7B-exl2-6_5 --local-dir-use-symlinks False