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

Code before:
            "model.embedding",                           # mamba-qbert
            "backbone.embedding",                        # mamba
            "backbone.embeddings",                       # mamba-hf
            "transformer.in_out_embed",                  # Grok
            "embedding.word_embeddings",                 # chatglm
            "transformer.token_embeddings",              # openelm
            "shared",                                    # t5
            "rwkv.embeddings",                           # rwkv6
            "model.embeddings",                          # rwkv7
            "model.word_embeddings",                     # bailingmoe
            "language_model.model.embed_tokens",         # llama4
            "encoder",                                   # neobert
            "model.transformer.wte",                     # llada
            "embed_tokens",                              # qwen3-embedding
        ),

        # Token type embeddings
        MODEL_TENSOR.TOKEN_TYPES: (
            "embeddings.token_type_embeddings",  # bert nomic-bert
        ),

        # Normalization of token embeddings
        MODEL_TENSOR.TOKEN_EMBD_NORM: (
            "word_embeddings_layernorm",  # bloom
            "embeddings.LayerNorm",       # bert
            "embeddings.norm",            # modern bert
            "emb_ln",                     # nomic-bert
            "transformer.norm",           # openelm
            "rwkv.blocks.0.pre_ln",       # rwkv
            "rwkv.blocks.0.pre_ln",       # rwkv6
            "model.pre_ln",               # rwkv7
            "model.layers.0.pre_norm",    # rwkv7
            "backbone.norm",              # wavtokenizer
            "model.embedding_norm",       # lfm2
        ),

        # Position embeddings
        MODEL_TENSOR.POS_EMBD: (
            "transformer.wpe",                 # gpt2
            "embeddings.position_embeddings",  # bert
            "wpe",                             # gpt2
        ),

        # Output
        MODEL_TENSOR.OUTPUT: (
            "embed_out",                 # gptneox
            "lm_head",                   # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx jais nemotron exaone olmoe olmo2 phimoe plamo2
            "output",                    # llama-pth bloom internlm2
            "word_embeddings_for_head",  # persimmon
            "lm_head.linear",            # phi2
            "output_layer",              # chatglm

Review comment (suggestion):
```suggestion
            "embeddings.norm",            # modern-bert
```

Code after:
            "model.embedding",                           # mamba-qbert
            "backbone.embedding",                        # mamba
            "backbone.embeddings",                       # mamba-hf
            "transformer.in_out_embed",                  # Grok
            "embedding.word_embeddings",                 # chatglm
            "transformer.token_embeddings",              # openelm
            "shared",                                    # t5
            "rwkv.embeddings",                           # rwkv6
            "model.embeddings",                          # rwkv7
            "model.word_embeddings",                     # bailingmoe
            "language_model.model.embed_tokens",         # llama4
            "encoder",                                   # neobert
            "model.transformer.wte",                     # llada
            "embed_tokens",                              # qwen3-embedding
        ),

        # Token type embeddings
        MODEL_TENSOR.TOKEN_TYPES: (
            "embeddings.token_type_embeddings",  # bert nomic-bert
        ),

        # Normalization of token embeddings
        MODEL_TENSOR.TOKEN_EMBD_NORM: (
            "word_embeddings_layernorm",  # bloom
            "embeddings.LayerNorm",       # bert
            "embeddings.norm",            # modern-bert
            "emb_ln",                     # nomic-bert
            "transformer.norm",           # openelm
            "rwkv.blocks.0.pre_ln",       # rwkv
            "rwkv.blocks.0.pre_ln",       # rwkv6
            "model.pre_ln",               # rwkv7
            "model.layers.0.pre_norm",    # rwkv7
            "backbone.norm",              # wavtokenizer
            "model.embedding_norm",       # lfm2
        ),

        # Position embeddings
        MODEL_TENSOR.POS_EMBD: (
            "transformer.wpe",                 # gpt2
            "embeddings.position_embeddings",  # bert
            "wpe",                             # gpt2
        ),

        # Output
        MODEL_TENSOR.OUTPUT: (
            "embed_out",                 # gptneox
            "lm_head",                   # gpt2 mpt falcon llama-hf baichuan qwen mamba dbrx jais nemotron exaone olmoe olmo2 phimoe plamo2
            "output",                    # llama-pth bloom internlm2
            "word_embeddings_for_head",  # persimmon
            "lm_head.linear",            # phi2
            "output_layer",              # chatglm