mtmd, model: allow skip build_vit() (#24077)

* add model

* nits

src/models/gemma4.cpp

@@ -142,6 +142,31 @@ static ggml_tensor * ggml_view_2d_slice(ggml_context * ctx0, ggml_tensor * x, in
                         idx * x->ne[0] * x->ne[1] * ggml_element_size(x));
 }
 
+// TODO @ngxson : maybe improve this in the future
+class llm_graph_input_logits_bias : public llm_graph_input_i {
+public:
+    llm_graph_input_logits_bias(const llama_vocab & vocab) {
+        arr.resize(vocab.n_tokens(), 0.0f);
+        for (llama_token id : vocab.get_suppress_tokens()) {
+            if (0 <= id && id < (int32_t)vocab.n_tokens()) {
+                arr[id] = -INFINITY;
+            }
+        }
+    }
+    virtual ~llm_graph_input_logits_bias() = default;
+
+    void set_input(const llama_ubatch *) override {
+        const int64_t n_vocab = arr.size();
+        ggml_backend_tensor_set(logits_bias, arr.data(), 0, n_vocab*ggml_element_size(logits_bias));
+    }
+
+    // bool can_reuse(const llm_graph_params & params) override;
+
+    ggml_tensor * logits_bias = nullptr; // F32 [n_vocab]
+
+    std::vector<float> arr;
+};
+
 llama_model_gemma4::graph::graph(const llama_model & model, const llm_graph_params & params) :
         llm_graph_context(params),
         model(model),
@@ -388,6 +413,16 @@ llama_model_gemma4::graph::graph(const llama_model & model, const llm_graph_para
         cur = ggml_scale(ctx0, cur, hparams.f_final_logit_softcapping);
     }
 
+    // apply logits bias if needed (e.g. for gemma4_unified patch)
+    // this is to mirror the suppress_tokens patch on transformers, to avoid model from outputing <image|> and <audio|> tokens (which is a known issue related to the checkpoint)
+    // TODO: maybe handle this inside the sampling system in the future
+    if (!model.vocab.get_suppress_tokens().empty()) {
+        auto inp_bias = std::make_unique<llm_graph_input_logits_bias>(model.vocab);
+        inp_bias->logits_bias = ggml_new_tensor_1d(ctx0, GGML_TYPE_F32, inp_bias->arr.size());
+        cur = ggml_add(ctx0, cur, inp_bias->logits_bias);
+        res->add_input(std::move(inp_bias));
+    }
+
     cb(cur, "result_output", -1);
     res->t_logits = cur;