fix model load

Author: ngxson

tools/mtmd/clip.cpp

@@ -2776,6 +2776,7 @@ struct clip_model_loader {
                 } break;
             case PROJECTOR_TYPE_LFM2:
             case PROJECTOR_TYPE_KIMIVL:
+            case PROJECTOR_TYPE_PADDLEOCR:
                 {
                     model.mm_input_norm_w = get_tensor(TN_MM_INP_NORM);
                     model.mm_input_norm_b = get_tensor(TN_MM_INP_NORM_B);
@@ -2840,27 +2841,6 @@ struct clip_model_loader {
                     model.mm_model_mlp_1_w = get_tensor(string_format(TN_MVLM_PROJ_MLP, 1, "weight"));
                     model.mm_model_mlp_2_w = get_tensor(string_format(TN_MVLM_PROJ_MLP, 2, "weight"));
                 } break;
-            case PROJECTOR_TYPE_PADDLEOCR:
-                {
-                    model.mm_model_query     = get_tensor(TN_RESAMPL_QUERY);
-                    model.mm_model_attn_q_w  = get_tensor(string_format(TN_RESAMPL_ATTN, "q", "weight"));
-                    model.mm_model_attn_k_w  = get_tensor(string_format(TN_RESAMPL_ATTN, "k", "weight"));
-                    model.mm_model_attn_v_w  = get_tensor(string_format(TN_RESAMPL_ATTN, "v", "weight"));
-                    model.mm_model_attn_q_b  = get_tensor(string_format(TN_RESAMPL_ATTN, "q", "bias"));
-                    model.mm_model_attn_k_b  = get_tensor(string_format(TN_RESAMPL_ATTN, "k", "bias"));
-                    model.mm_model_attn_v_b  = get_tensor(string_format(TN_RESAMPL_ATTN, "v", "bias"));
-                    model.mm_model_attn_o_w  = get_tensor(string_format(TN_RESAMPL_ATTN, "out", "weight"));
-                    model.mm_model_attn_o_b  = get_tensor(string_format(TN_RESAMPL_ATTN, "out", "bias"));
-                    model.mm_model_ln_post_w = get_tensor(string_format(TN_RESAMPL_LN, "post", "weight"));
-                    model.mm_model_ln_post_b = get_tensor(string_format(TN_RESAMPL_LN, "post", "bias"));
-                    // projector ffn
-                    model.mm_1_w = get_tensor(string_format(TN_LLAVA_PROJ, 1, "weight"));
-                    model.mm_1_b = get_tensor(string_format(TN_LLAVA_PROJ, 1, "bias"));
-                    model.mm_2_w = get_tensor(string_format(TN_LLAVA_PROJ, 2, "weight"));
-                    model.mm_2_b = get_tensor(string_format(TN_LLAVA_PROJ, 2, "bias"));
-                    model.mm_input_norm_w = get_tensor(TN_MM_INP_NORM);
-                    model.mm_input_norm_b = get_tensor(TN_MM_INP_NORM_B);
-                } break;
             default:
                 GGML_ASSERT(false && "unknown projector type");
         }