vbatts/llama.cpp
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Show warning when using a quantized base model

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Slaren 2023-04-15 20:11:07 +02:00
parent fc89916002
commit 14858ba2bf
1 changed files with 10 additions and 3 deletions
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13
llama.cpp
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@ -1843,9 +1843,8 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
model_loader->mapping.reset(new llama_mmap(&model_loader->file_loaders.at(0)->file, false)); model_loader->mapping.reset(new llama_mmap(&model_loader->file_loaders.at(0)->file, false));
} }
fprintf(stderr, "%s: ", __func__);
// read tensors and apply // read tensors and apply
bool warned = false;
int n_tensors = 0; int n_tensors = 0;
while (true) { while (true) {
int32_t n_dims; int32_t n_dims;
@ -1938,6 +1937,14 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
base_t = dest_t; base_t = dest_t;
} }
if (base_t->type == GGML_TYPE_Q4_0 || base_t->type == GGML_TYPE_Q4_1) {
if (!warned) {
fprintf(stderr, "%s: warning: using a lora adapter with a quantized model may result in poor quality, "
"use a f16 or f32 base model with --lora-base\n", __func__);
warned = true;
}
}
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"];
@ -1974,7 +1981,7 @@ int llama_apply_lora_from_file_internal(struct llama_context * ctx, const char *
lora_tensors.clear(); lora_tensors.clear();
n_tensors++; n_tensors++;
if (n_tensors % 8 == 0) if (n_tensors % 4 == 0)
fprintf(stderr, "."); fprintf(stderr, ".");
} }
} }