[pull] master from ggml-org:master

.github/workflows/ui-publish.yml

@@ -13,8 +13,13 @@ on:
         required: true
 
 jobs:
+  build:
+    name: Build static output
+    uses: ./.github/workflows/ui-build.yml
+
   publish:
     name: Publish UI Static Output
+    needs: build
     runs-on: ubuntu-24.04-arm
 
     permissions:

src/llama-model-saver.cpp

@@ -393,6 +393,8 @@ void llama_model_saver::add_tensors_from_model() {
     add_tensor(model->output);
     add_tensor(model->output_b);
     add_tensor(model->output_norm_enc);
+    add_tensor(model->output_s);
+    add_tensor(model->output_in_s);
     add_tensor(model->cls);
     add_tensor(model->cls_b);
     add_tensor(model->cls_out);

src/llama-model.cpp

@@ -1394,10 +1394,23 @@ bool llama_model_base::load_tensors(llama_model_loader & ml) {
                 layer.ssm_beta_in_s = create_tensor(tn(LLM_TENSOR_SSM_BETA, "input_scale", i), {1}, TENSOR_NOT_REQUIRED);
             }
         }
+        // output scales
+        if (output && output->type == GGML_TYPE_NVFP4) {
+            // weight scale
+            if (!output_s) {
+                output_s = create_tensor(tn(LLM_TENSOR_OUTPUT, "scale"), {1}, TENSOR_NOT_REQUIRED);
+            }
+            // input scale
+            if (!output_in_s) {
+                output_in_s = create_tensor(tn(LLM_TENSOR_OUTPUT, "input_scale"), {1}, TENSOR_NOT_REQUIRED);
+            }
+        }
     }
-
     ml.done_getting_tensors();
 
+    GGML_ASSERT(!(output && tok_embd &&
+            strcmp(output->name, tok_embd->name) == 0 &&
+            output->type == GGML_TYPE_NVFP4));
     // populate tensors_by_name
     for (auto & [_, ctx_ptr] : ml.ctx_map) {
         for (auto * cur = ggml_get_first_tensor(ctx_ptr.get()); cur != NULL; cur = ggml_get_next_tensor(ctx_ptr.get(), cur)) {

src/llama-model.h

@@ -533,6 +533,11 @@ struct llama_model {
     struct ggml_tensor * output_b        = nullptr;
     struct ggml_tensor * output_norm_enc = nullptr;
 
+
+    // NVFP4 per-tensor scale2, input_scale for LM head
+    struct ggml_tensor * output_s    = nullptr;
+    struct ggml_tensor * output_in_s = nullptr;
+
     // classifier
     struct ggml_tensor * cls       = nullptr;
     struct ggml_tensor * cls_b     = nullptr;

src/models/afmoe.cpp

@@ -277,7 +277,7 @@ llama_model_afmoe::graph::graph(const llama_model & model, const llm_graph_param
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
     cb(cur, "result_output", -1);
     res->t_logits = cur;
 

src/models/apertus.cpp

@@ -160,7 +160,7 @@ llama_model_apertus::graph::graph(const llama_model & model, const llm_graph_par
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/arcee.cpp

@@ -148,7 +148,7 @@ llama_model_arcee::graph::graph(const llama_model & model, const llm_graph_param
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/arctic.cpp

@@ -171,7 +171,7 @@ llama_model_arctic::graph::graph(const llama_model & model, const llm_graph_para
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/arwkv7.cpp

@@ -193,7 +193,7 @@ llama_model_arwkv7::graph::graph(const llama_model & model, const llm_graph_para
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/baichuan.cpp

@@ -146,7 +146,7 @@ llama_model_baichuan::graph::graph(const llama_model & model, const llm_graph_pa
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/bailingmoe.cpp

@@ -171,7 +171,7 @@ llama_model_bailingmoe::graph::graph(const llama_model & model, const llm_graph_
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/bailingmoe2.cpp

@@ -210,7 +210,7 @@ llama_model_bailingmoe2::graph::graph(const llama_model & model, const llm_graph
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/bloom.cpp

@@ -142,7 +142,7 @@ llama_model_bloom::graph::graph(const llama_model & model, const llm_graph_param
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/chameleon.cpp

@@ -181,7 +181,7 @@ llama_model_chameleon::graph::graph(const llama_model & model, const llm_graph_p
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
     cb(cur, "result_output_with_img_logits", -1);
 
     // TODO: this suppresses the output of image tokens, which is required to enable text-only outputs.

src/models/chatglm.cpp

@@ -151,7 +151,7 @@ llama_model_chatglm::graph::graph(const llama_model & model, const llm_graph_par
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/codeshell.cpp

@@ -143,7 +143,7 @@ llama_model_codeshell::graph::graph(const llama_model & model, const llm_graph_p
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/cogvlm.cpp

@@ -150,7 +150,7 @@ llama_model_cogvlm::graph::graph(const llama_model & model, const llm_graph_para
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
     cb(cur, "result_output", -1);
     res->t_logits = cur;
     ggml_build_forward_expand(gf, cur);

src/models/cohere2.cpp

@@ -146,7 +146,7 @@ llama_model_cohere2::graph::graph(const llama_model & model, const llm_graph_par
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     if (f_logit_scale) {
         cur = ggml_scale(ctx0, cur, f_logit_scale);

src/models/command-r.cpp

@@ -131,7 +131,7 @@ llama_model_command_r::graph::graph(const llama_model & model, const llm_graph_p
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     if (f_logit_scale) {
         cur = ggml_scale(ctx0, cur, f_logit_scale);

src/models/dbrx.cpp

@@ -145,7 +145,7 @@ llama_model_dbrx::graph::graph(const llama_model & model, const llm_graph_params
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/deci.cpp

@@ -181,7 +181,7 @@ llama_model_deci::graph::graph(const llama_model & model, const llm_graph_params
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/deepseek.cpp

@@ -185,7 +185,7 @@ llama_model_deepseek::graph::graph(const llama_model & model, const llm_graph_pa
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/dots1.cpp

@@ -183,7 +183,7 @@ llama_model_dots1::graph::graph(const llama_model & model, const llm_graph_param
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/dream.cpp

@@ -128,7 +128,7 @@ llama_model_dream::graph::graph(const llama_model & model, const llm_graph_param
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/ernie4-5-moe.cpp

@@ -124,7 +124,7 @@ llama_model_ernie4_5_moe::graph::graph(const llama_model & model, const llm_grap
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/ernie4-5.cpp

@@ -155,7 +155,7 @@ llama_model_ernie4_5::graph::graph(const llama_model & model, const llm_graph_pa
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/exaone-moe.cpp

@@ -237,7 +237,7 @@ llama_model_exaone_moe::graph::graph(const llama_model & model, const llm_graph_
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/exaone.cpp

@@ -127,7 +127,7 @@ llama_model_exaone::graph::graph(const llama_model & model, const llm_graph_para
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/exaone4.cpp

@@ -163,7 +163,7 @@ llama_model_exaone4::graph<iswa>::graph(const llama_model & model, const llm_gra
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/falcon-h1.cpp

@@ -200,7 +200,7 @@ llama_model_falcon_h1::graph::graph(const llama_model & model, const llm_graph_p
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/falcon.cpp

@@ -152,7 +152,7 @@ llama_model_falcon::graph::graph(const llama_model & model, const llm_graph_para
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/gemma.cpp

@@ -130,7 +130,7 @@ llama_model_gemma::graph::graph(const llama_model & model, const llm_graph_param
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/gemma2.cpp

@@ -163,7 +163,7 @@ llama_model_gemma2::graph::graph(const llama_model & model, const llm_graph_para
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     // final logit soft-capping
     cur = ggml_scale(ctx0, cur, 1.0f / hparams.f_final_logit_softcapping);

src/models/gemma3.cpp

@@ -207,7 +207,7 @@ llama_model_gemma3::graph<iswa>::graph(const llama_model & model, const llm_grap
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     if (hparams.f_final_logit_softcapping) {
         cur = ggml_scale(ctx0, cur, 1.0f / hparams.f_final_logit_softcapping);

src/models/gemma3n.cpp

@@ -296,7 +296,7 @@ llama_model_gemma3n::graph::graph(const llama_model & model, const llm_graph_par
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     {
         // final logit soft-capping

src/models/gemma4.cpp

@@ -380,7 +380,7 @@ llama_model_gemma4::graph::graph(const llama_model & model, const llm_graph_para
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     if (hparams.f_final_logit_softcapping) {
         cur = ggml_scale(ctx0, cur, 1.0f / hparams.f_final_logit_softcapping);

src/models/glm4-moe.cpp

@@ -275,7 +275,7 @@ llama_model_glm4_moe::graph::graph(const llama_model & model, const llm_graph_pa
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/glm4.cpp

@@ -185,7 +185,7 @@ llama_model_glm4::graph::graph(const llama_model & model, const llm_graph_params
     res->t_embd = cur;
 
     // Output projection
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/gpt2.cpp

@@ -138,7 +138,7 @@ llama_model_gpt2::graph::graph(const llama_model & model, const llm_graph_params
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/gptneox.cpp

@@ -209,7 +209,7 @@ llama_model_gptneox::graph::graph(const llama_model & model, const llm_graph_par
     cb(cur, "result_norm", -1);
     res->t_embd = cur;
 
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     cb(cur, "result_output", -1);
     res->t_logits = cur;

src/models/granite-hybrid.cpp

@@ -186,7 +186,7 @@ llama_model_granite_hybrid::graph::graph(const llama_model & model, const llm_gr
     res->t_embd = cur;
 
     // lm_head
-    cur = build_lora_mm(model.output, cur);
+    cur = build_lora_mm(model.output, cur, model.output_s);
 
     // For Granite architectures - scale logits
     if (hparams.f_logit_scale) {