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README.md
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@@ -17,7 +17,7 @@ For more details, see github repo [tctsung/LLM_quantize](https://github.com/tcts
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2. The model size was compressed from 4.4GB to 0.78GB, representing a reduction in memory footprint to only **17.57%** of the original model.
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3. I used 6 different LLM tasks to demonstrate that the quantized model maintains similar accuracy, with a maximum accuracy degradation of only ~1%
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## Inference tutorial
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2. The model size was compressed from 4.4GB to 0.78GB, representing a reduction in memory footprint to only **17.57%** of the original model.
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3. I used 6 different LLM tasks to demonstrate that the quantized model maintains similar accuracy, with a maximum accuracy degradation of only ~1%
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<Gallery />
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## Inference tutorial
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