vbatts/llama.cpp
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fix

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jon-chuang 2023-04-26 23:29:26 +08:00
parent 4afcc37869
commit 7ffbcbdfa3
1 changed files with 4 additions and 4 deletions
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llama.cpp
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@ -2017,14 +2017,14 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
ggml_tensor * loraA = lora_tensors[base_name + ".loraA"]; ggml_tensor * loraA = lora_tensors[base_name + ".loraA"];
ggml_tensor * loraB = lora_tensors[base_name + ".loraB"]; ggml_tensor * loraB = lora_tensors[base_name + ".loraB"];
if (base_t->ne[0] != loraA->ne[1] || base_t->ne[1] != loraB->ne[1]) { if (base_t->ne[0] != loraB->ne[1] || base_t->ne[1] != loraA->ne[1]) {
fprintf(stderr, "%s: incompatible tensor dimensions (%" PRId64 " and %" PRId64 ");" fprintf(stderr, "%s: incompatible tensor dimensions (outdims: %" PRId64 ", %" PRId64 ", indims: );"
" are you sure that this adapter is for this model?\n", __func__, base_t->ne[0], loraA->ne[1]); " are you sure that this adapter is for this model?\n", __func__, base_t->ne[0], loraB->ne[1], base_t->ne[1], loraA->ne[1]);
return 1; return 1;
} }
// w = w + BA*s // w = w + BA*s
ggml_tensor * BA = ggml_mul_mat(lora_ctx, loraA, loraB); ggml_tensor * BA = ggml_mul_mat(lora_ctx, loraB, loraA);
if (scaling != 1.0f) { if (scaling != 1.0f) {
ggml_tensor * scale_tensor = ggml_new_f32(lora_ctx, scaling); ggml_tensor * scale_tensor = ggml_new_f32(lora_ctx, scaling);