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README.md
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@@ -24,6 +24,41 @@ These quants were made with exllamav2 version 0.0.18. Quants made on this versio
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If you have problems loading these models, please update Text Generation WebUI to the latest version.
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## Quant Details
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If you have problems loading these models, please update Text Generation WebUI to the latest version.
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## Perplexity Scoring
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Below are the perplexity scores for the EXL2 models. A lower score is better.
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_TODO:_ Coming soon
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### Perplexity Script
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This was the script used for perplexity testing.
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```bash
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#!/bin/bash
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source ~/miniconda3/etc/profile.d/conda.sh
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conda activate exllamav2
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# Set the model name and bit size
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MODEL_NAME="CodeQwen1.5-7B-Chat"
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BIT_PRECISIONS=(8.0 7.0 6.0 5.0 4.0 3.5 3.0 2.75 2.5)
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# Print the markdown table header
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echo "| Quant Level | Perplexity Score |"
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echo "|-------------|------------------|"
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for BIT_PRECISION in "${BIT_PRECISIONS[@]}"
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do
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MODEL_DIR="models/${MODEL_NAME}_exl2_${BIT_PRECISION}bpw"
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if [ -d "$MODEL_DIR" ]; then
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output=$(python test_inference.py -m "$MODEL_DIR" -gs 17,24 -ed data/wikitext/wikitext-2-v1.parquet)
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score=$(echo "$output" | grep -oP 'Evaluation perplexity: \K[\d.]+')
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echo "| $BIT_PRECISION | $score |"
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fi
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done
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```
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## Quant Details
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