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Merge branch 'upstream' into concedo_experimental
# Conflicts: # .github/workflows/gguf-publish.yml # CODEOWNERS # examples/sycl/test.sh # pyproject.toml # tools/mtmd/CMakeLists.txt # tools/mtmd/README.md
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@@ -415,7 +415,7 @@ static llama_model * llama_model_mapping(llm_arch arch, const llama_model_params
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case LLM_ARCH_STEP35:
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return new llama_model_step35(params);
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default:
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GGML_ABORT("unimplemented model class");
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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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}
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@@ -1802,6 +1802,7 @@ void llama_model::print_info() const {
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LLAMA_LOG_INFO("%s: f_max_alibi_bias = %.1e\n", __func__, hparams.f_max_alibi_bias);
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LLAMA_LOG_INFO("%s: f_logit_scale = %.1e\n", __func__, hparams.f_logit_scale);
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LLAMA_LOG_INFO("%s: f_attn_scale = %.1e\n", __func__, hparams.f_attention_scale);
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LLAMA_LOG_INFO("%s: f_attn_value_scale = %.4f\n", __func__, hparams.f_attn_value_scale);
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LLAMA_LOG_INFO("%s: n_ff = %s\n", __func__, print_f([&](uint32_t il) { return hparams.n_ff(il); }, hparams.n_layer).c_str());
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LLAMA_LOG_INFO("%s: n_expert = %u\n", __func__, hparams.n_expert);
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LLAMA_LOG_INFO("%s: n_expert_used = %u\n", __func__, hparams.n_expert_used);
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