Repository: ggerganov/llama.cpp
File: gguf-py/gguf/tensor_mapping.py (Python)

Code before:
        MODEL_TENSOR.V_MMPROJ_FC: (
            "model.connector.modality_projection.proj", # SmolVLM
        ),

        MODEL_TENSOR.V_MMPROJ_MLP: (
            "model.mm_projector.mlp.mlp.{bid}",
            "vision_model.vision_adapter.mlp.fc{bid}", # llama 4
            "mlp1.{bid}", # InternVL
            "model.aligner.fc1.hidden_layers.{bid}", # Janus Pro
        ),

        MODEL_TENSOR.V_MMPROJ_PEG: (
            "model.mm_projector.peg.peg.{bid}",
        ),

        MODEL_TENSOR.V_ENC_EMBD_CLS: (
            "vision_tower.vision_model.embeddings.class_embedding",
            "model.vision_tower.embeddings.cls_token", # Intern-S1
            "vision_model.class_embedding", # llama 4
        ),

        MODEL_TENSOR.V_ENC_EMBD_PATCH: (
            "vision_tower.vision_model.embeddings.patch_embedding",
            "model.vision_tower.embeddings.patch_embeddings.projection", # Intern-S1
            "vpm.embeddings.patch_embedding",
            "model.vision_model.embeddings.patch_embedding", # SmolVLM, Janus Pro
            "vision_tower.patch_conv", # pixtral-hf
            "vision_encoder.patch_conv", # pixtral
            "vision_model.patch_embedding.linear", # llama 4
            "visual.patch_embed.proj", # qwen2vl
            "vision_tower.patch_embed.proj", # kimi-vl
        ),

        MODEL_TENSOR.V_ENC_EMBD_POS: (
            "vision_tower.vision_model.embeddings.position_embedding",
            "model.vision_tower.embeddings.position_embeddings", # Intern-S1
            "vpm.embeddings.position_embedding",
            "model.vision_model.embeddings.position_embedding", # SmolVLM, Janus Pro
            "vision_model.positional_embedding_vlm", # llama 4
            "vision_tower.patch_embed.pos_emb", # kimi-vl
        ),

        MODEL_TENSOR.V_ENC_ATTN_Q: (
            "vision_tower.vision_model.encoder.layers.{bid}.self_attn.q_proj",
            "model.vision_tower.encoder.layer.{bid}.attention.q_proj", # Intern-S1
            "vpm.encoder.layers.{bid}.self_attn.q_proj",
            "model.vision_model.encoder.layers.{bid}.self_attn.q_proj", # SmolVLM
            "vision_model.model.layers.{bid}.self_attn.q_proj", # llama4
            "vision_tower.transformer.layers.{bid}.attention.q_proj", # pixtral-hf
            "vision_encoder.transformer.layers.{bid}.attention.wq", # pixtral
            "visual.blocks.{bid}.attn.q", # qwen2vl, generated

Review comment (suggestion):
```suggestion
            "model.vision_model.embeddings.patch_embedding", # SmolVLM
```
No need to stack on for every model, the list will get very long that way. :)

Code after:
        MODEL_TENSOR.POSNET_ATTN_V: (
            "backbone.posnet.{bid}.v", # wavtokenizer
        ),

        MODEL_TENSOR.POSNET_ATTN_OUT: (
            "backbone.posnet.{bid}.proj_out", # wavtokenizer
        ),

        MODEL_TENSOR.SHORTCONV_CONV: (
            "model.layers.{bid}.conv.conv",
        ),

        MODEL_TENSOR.SHORTCONV_INPROJ: (
            "model.layers.{bid}.conv.in_proj",
        ),

        MODEL_TENSOR.SHORTCONV_OUTPROJ: (
            "model.layers.{bid}.conv.out_proj",
        ),

        #############################################################################
        ## Vision encoder

        MODEL_TENSOR.V_MMPROJ: (
            "multi_modal_projector.linear_{bid}",
            "visual.merger.mlp.{bid}", # qwen2vl
        ),

        MODEL_TENSOR.V_MMPROJ_FC: (
            "model.connector.modality_projection.proj", # SmolVLM
            "model.vision.linear_proj.linear_proj", # cogvlm
        ),

        MODEL_TENSOR.V_MMPROJ_MLP: (
            "model.mm_projector.mlp.mlp.{bid}",
            "vision_model.vision_adapter.mlp.fc{bid}", # llama 4
            "mlp1.{bid}", # InternVL
            "model.aligner.fc1.hidden_layers.{bid}", # Janus Pro
        ),

        MODEL_TENSOR.V_MMPROJ_PEG: (
            "model.mm_projector.peg.peg.{bid}",
        ),

        MODEL_TENSOR.V_ENC_EMBD_CLS: (
            "vision_tower.vision_model.embeddings.class_embedding",
            "model.vision_tower.embeddings.cls_token", # Intern-S1
            "vision_model.class_embedding", # llama 4
            "model.vision.patch_embedding.cls_embedding", # cogvlm
        ),