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@ -768,7 +768,7 @@ The time per token is measured on a MacBook M1 Pro 32GB RAM using 4 and 8 thread
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#### How to run
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1. Download/extract: https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip?ref=salesforce-research
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1. Download/extract: https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
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2. Run `./perplexity -m models/7B/ggml-model-q4_0.gguf -f wiki.test.raw`
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3. Output:
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```
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@ -219,7 +219,7 @@ function gg_run_open_llama_3b_v2 {
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gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/resolve/main/pytorch_model.bin
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gg_wget models-mnt/open-llama/3B-v2/ https://huggingface.co/openlm-research/open_llama_3b_v2/raw/main/generation_config.json
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gg_wget models-mnt/wikitext/ https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip
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gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
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unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
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head -n 60 models-mnt/wikitext/wikitext-2-raw/wiki.test.raw > models-mnt/wikitext/wikitext-2-raw/wiki.test-60.raw
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@ -401,7 +401,7 @@ function gg_run_open_llama_7b_v2 {
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gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/resolve/main/pytorch_model-00002-of-00002.bin
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gg_wget models-mnt/open-llama/7B-v2/ https://huggingface.co/openlm-research/open_llama_7b_v2/raw/main/generation_config.json
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gg_wget models-mnt/wikitext/ https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip
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gg_wget models-mnt/wikitext/ https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
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unzip -o models-mnt/wikitext/wikitext-2-raw-v1.zip -d models-mnt/wikitext/
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path_models="../models-mnt/open-llama/7B-v2"
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@ -309,7 +309,7 @@ static void process_logits(int n_vocab, const float * logits, const int * tokens
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}
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static results_perplexity perplexity_v2(llama_context * ctx, const gpt_params & params) {
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// Download: https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip?ref=salesforce-research
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// Download: https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
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// Run `./perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
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// Output: `perplexity: 13.5106 [114/114]`
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// BOS tokens will be added for each chunk before eval
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@ -447,7 +447,7 @@ static results_perplexity perplexity(llama_context * ctx, const gpt_params & par
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return perplexity_v2(ctx, params);
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}
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// Download: https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip?ref=salesforce-research
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// Download: https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
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// Run `./perplexity -m models/7B/ggml-model-q4_0.bin -f wiki.test.raw`
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// Output: `perplexity: 13.5106 [114/114]`
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// BOS tokens will be added for each chunk before eval
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@ -1837,9 +1837,9 @@ static void quantize_row_q2_K_impl(const float * restrict x, block_q2_K * restri
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float sigma2 = sumx2/QK_K;
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for (int j = 0; j < QK_K/16; ++j) {
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const float * restrict qw = quant_weights + QK_K * i + 16*j;
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for (int l = 0; l < 16; ++l) weight[l] = qw[l] * sqrtf(sigma2 + x[16*j + l]*x[16*j + l]);
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for (int l = 0; l < 16; ++l) sw[j] += weight[l];
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scales[j] = make_qkx3_quants(16, 3, x + 16*j, weight, L + 16*j, &mins[j], Laux, -0.9f, 0.05f, 36, false);
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for (int l = 0; l < QK_K/16; ++l) weight[l] = qw[l] * sqrtf(sigma2 + x[16*j + l]*x[16*j + l]);
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for (int l = 0; l < QK_K/16; ++l) sw[j] += weight[l];
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scales[j] = make_qkx3_quants(QK_K/16, 3, x + 16*j, weight, L + 16*j, &mins[j], Laux, -0.9f, 0.05f, 36, false);
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}
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float dm = make_qp_quants(QK_K/16, 15, scales, Ls, sw);
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@ -1,6 +1,6 @@
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#!/bin/bash
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wget https://s3.amazonaws.com/research.metamind.io/wikitext/wikitext-2-raw-v1.zip
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wget https://huggingface.co/datasets/ggml-org/ci/resolve/main/wikitext-2-raw-v1.zip
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echo "Usage:"
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echo ""
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