diff options
Diffstat (limited to 'gguf-py/gguf/tensor_mapping.py')
| -rw-r--r-- | gguf-py/gguf/tensor_mapping.py | 13 |
1 files changed, 10 insertions, 3 deletions
diff --git a/gguf-py/gguf/tensor_mapping.py b/gguf-py/gguf/tensor_mapping.py index 4f16d850..c7ba1420 100644 --- a/gguf-py/gguf/tensor_mapping.py +++ b/gguf-py/gguf/tensor_mapping.py @@ -30,6 +30,7 @@ class TensorNameMap: # Normalization of token embeddings MODEL_TENSOR.TOKEN_EMBD_NORM: ( "word_embeddings_layernorm", # bloom + "embeddings.LayerNorm", # bert ), # Position embeddings @@ -54,7 +55,6 @@ class TensorNameMap: "transformer.ln_f", # gpt2 gpt-j falcon "model.norm", # llama-hf baichuan internlm2 "norm", # llama-pth - "embeddings.LayerNorm", # bert "transformer.norm_f", # mpt "ln_f", # refact bloom qwen gpt2 "language_model.encoder.final_layernorm", # persimmon @@ -79,7 +79,6 @@ class TensorNameMap: "transformer.h.{bid}.ln_mlp", # falcon40b "model.layers.{bid}.input_layernorm", # llama-hf "layers.{bid}.attention_norm", # llama-pth - "encoder.layer.{bid}.attention.output.LayerNorm", # bert "language_model.encoder.layers.{bid}.input_layernorm", # persimmon "model.layers.{bid}.ln1", # yi "h.{bid}.ln_1", # gpt2 @@ -155,6 +154,11 @@ class TensorNameMap: "model.layers.{bid}.attention.wo", # internlm2 ), + # Attention output norm + MODEL_TENSOR.ATTN_OUT_NORM: ( + "encoder.layer.{bid}.attention.output.LayerNorm", # bert + ), + # Rotary embeddings MODEL_TENSOR.ATTN_ROT_EMBD: ( "model.layers.{bid}.self_attn.rotary_emb.inv_freq", # llama-hf @@ -171,7 +175,6 @@ class TensorNameMap: "transformer.blocks.{bid}.norm_2", # mpt "model.layers.{bid}.post_attention_layernorm", # llama-hf "layers.{bid}.ffn_norm", # llama-pth - "encoder.layer.{bid}.output.LayerNorm", # bert "language_model.encoder.layers.{bid}.post_attention_layernorm", # persimmon "model.layers.{bid}.ln2", # yi "h.{bid}.ln_2", # gpt2 @@ -266,6 +269,10 @@ class TensorNameMap: MODEL_TENSOR.ROPE_FREQS: ( "language_model.encoder.layers.{bid}.self_attention.rotary_emb.inv_freq", # persimmon ), + + MODEL_TENSOR.LAYER_OUT_NORM: ( + "encoder.layer.{bid}.output.LayerNorm", # bert + ) } mapping: dict[str, tuple[MODEL_TENSOR, str]] |