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@@ -15304,7 +15304,7 @@ static ggml_type llama_tensor_get_type(quantize_state_internal & qs, ggml_type n
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const int n_expert = std::max(1, (int)qs.model.hparams.n_expert);
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auto layer_info = [n_expert] (int i_layer, int n_layer, const char * name) {
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if (n_expert > 1) {
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- // Believe it or not, "experts" in the FFN of Mixtral-8x7B are not consecutive, but iccasionally randomly
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+ // Believe it or not, "experts" in the FFN of Mixtral-8x7B are not consecutive, but occasionally randomly
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// sprinkled in the model. Hence, simply dividing i_ffn_down by n_expert does not work
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// for getting the current layer as I initially thought, and we need to resort to parsing the
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// tensor name.
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