Add details on dataset/context length
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@ -250,6 +250,9 @@ see https://huggingface.co/docs/transformers/perplexity. However, in general, l
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https://github.com/ggerganov/llama.cpp/pull/270 is the unofficial tracking page for now. llama.cpp is measuring very well
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https://github.com/ggerganov/llama.cpp/pull/270 is the unofficial tracking page for now. llama.cpp is measuring very well
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compared to the baseline implementations. Quantization has a small negative impact to quality, but, as you can see, running
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compared to the baseline implementations. Quantization has a small negative impact to quality, but, as you can see, running
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13B at q4_0 beats the 7B f16 model by a significant amount.
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13B at q4_0 beats the 7B f16 model by a significant amount.
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All measurements are done against wikitext2 test dataset (https://paperswithcode.com/dataset/wikitext-2), with default options (512 length context).
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Note that the changing the context length will have a significant impact on perplexity (longer context = better perplexity).
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```
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```
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Perplexity - model options
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Perplexity - model options
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5.5985 - 13B, q4_0
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5.5985 - 13B, q4_0
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