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talk-llama : sync llama.cpp
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@@ -157,6 +157,8 @@ static llama_model * llama_model_mapping(llm_arch arch, const llama_model_params
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return new llama_model_command_r(params);
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case LLM_ARCH_COHERE2:
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return new llama_model_cohere2(params);
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case LLM_ARCH_COHERE2MOE:
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return new llama_model_cohere2moe(params);
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case LLM_ARCH_DBRX:
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return new llama_model_dbrx(params);
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case LLM_ARCH_OLMO:
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@@ -1467,9 +1469,12 @@ bool llama_model_base::load_tensors(llama_model_loader & ml) {
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}
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ml.done_getting_tensors();
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// Tied NVFP4 output is valid when no separate LM-head scale tensors are present.
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// If sidecar scales exist, the output weight must be an actual output tensor.
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GGML_ASSERT(!(output && tok_embd &&
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strcmp(output->name, tok_embd->name) == 0 &&
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output->type == GGML_TYPE_NVFP4));
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output->type == GGML_TYPE_NVFP4 &&
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(output_s || output_in_s)));
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// populate tensors_by_name
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for (auto & [_, ctx_ptr] : ml.ctx_map) {
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for (auto * cur = ggml_get_first_tensor(ctx_ptr.get()); cur != NULL; cur = ggml_get_next_tensor(ctx_ptr.get(), cur)) {
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@@ -1844,6 +1849,7 @@ void llama_model::print_info() const {
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}
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if (arch == LLM_ARCH_MELLUM ||
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arch == LLM_ARCH_COHERE2MOE ||
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arch == LLM_ARCH_QWEN3MOE ||
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arch == LLM_ARCH_OPENAI_MOE ||
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arch == LLM_ARCH_QWEN3VLMOE ||
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@@ -2389,6 +2395,7 @@ llama_rope_type llama_model_rope_type(const llama_model * model) {
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case LLM_ARCH_XVERSE:
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case LLM_ARCH_COMMAND_R:
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case LLM_ARCH_COHERE2:
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case LLM_ARCH_COHERE2MOE:
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case LLM_ARCH_OLMO:
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case LLM_ARCH_ARCTIC:
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case LLM_ARCH_DEEPSEEK:
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