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+6
-3
@@ -312,6 +312,8 @@ static llama_model * llama_model_mapping(llm_arch arch, const llama_model_params
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return new llama_model_kimi_linear(params);
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case LLM_ARCH_STEP35:
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return new llama_model_step35(params);
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case LLM_ARCH_INKLING:
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return new llama_model_inkling(params);
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default:
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throw std::runtime_error(std::string("unsupported model architecture: '") + llm_arch_name(arch) + "'");
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}
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@@ -1356,8 +1358,8 @@ bool llama_model_base::load_tensors(llama_model_loader & ml) {
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}
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if (params.load_mode == LLAMA_LOAD_MODE_LONGHAUL) {
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if (arch != LLM_ARCH_QWEN35MOE && arch != LLM_ARCH_LAGUNA) {
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throw std::runtime_error("longhaul currently requires a qwen35moe or laguna model");
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if (arch != LLM_ARCH_QWEN35MOE && arch != LLM_ARCH_LAGUNA && arch != LLM_ARCH_INKLING) {
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throw std::runtime_error("longhaul currently requires a qwen35moe, laguna, or inkling model");
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}
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if (hparams.n_layer_nextn != 0) {
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throw std::runtime_error("longhaul does not support MTP tensors");
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@@ -2165,7 +2167,7 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
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// layer filters, so pick the right one here
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llama_memory_hybrid::layer_filter_cb filter_attn = nullptr;
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llama_memory_hybrid::layer_filter_cb filter_recr = nullptr;
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if (arch == LLM_ARCH_FALCON_H1) {
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if (arch == LLM_ARCH_FALCON_H1 || arch == LLM_ARCH_INKLING) {
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filter_attn = [&](uint32_t) { return true; };
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filter_recr = [&](uint32_t) { return true; };
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} else if (arch == LLM_ARCH_NEMOTRON_H || arch == LLM_ARCH_NEMOTRON_H_MOE) {
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@@ -2506,6 +2508,7 @@ llama_rope_type llama_model_rope_type(const llama_model * model) {
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case LLM_ARCH_NEMOTRON_H:
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case LLM_ARCH_NEMOTRON_H_MOE:
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case LLM_ARCH_KIMI_LINEAR:
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case LLM_ARCH_INKLING:
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return LLAMA_ROPE_TYPE_NONE;
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// use what we call a normal RoPE, operating on pairs of consecutive head values
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