nikola/llama_cpp
1
0
Fork 0
Code Issues Pull Requests Actions 22 Packages Projects Releases Wiki Activity

convert : add filter_tensors method to pre-filter tensors (#22597)

Browse Source 
* add filter_tensors classmethod

* remove language_model

* fix parts validation
This commit is contained in:
Sigbjørn Skjæret
2026-05-06 08:06:05 +02:00
committed by GitHub
parent 2ca1161bd7
commit 74d6248f71
2 changed files with 710 additions and 575 deletions
Download Patch File Download Diff File Expand all files Collapse all files
convert_hf_to_gguf.py
+617 -473
View File
File diff suppressed because it is too large Load Diff
gguf-py/gguf/tensor_mapping.py
+3 -12
View File
@@ -18,7 +18,6 @@ class TensorNameMap:
"tok_embeddings", # llama-pth "tok_embeddings", # llama-pth
"embeddings.word_embeddings", # bert nomic-bert "embeddings.word_embeddings", # bert nomic-bert
"embeddings.tok_embeddings", # modern-bert "embeddings.tok_embeddings", # modern-bert
"language_model.embedding.word_embeddings", # persimmon
"wte", # gpt2 "wte", # gpt2
"transformer.embd.wte", # phi2 "transformer.embd.wte", # phi2
"model.tok_embeddings", # internlm2 "model.tok_embeddings", # internlm2
@@ -32,7 +31,6 @@ class TensorNameMap:
"rwkv.embeddings", # rwkv6 "rwkv.embeddings", # rwkv6
"model.embeddings", # rwkv7 "model.embeddings", # rwkv7
"model.word_embeddings", # bailingmoe "model.word_embeddings", # bailingmoe
"language_model.model.embed_tokens", # llama4
"encoder", # neobert "encoder", # neobert
"model.transformer.wte", # llada "model.transformer.wte", # llada
"embed_tokens", # qwen3-embedding "embed_tokens", # qwen3-embedding
@@ -94,7 +92,6 @@ class TensorNameMap:
"norm", # llama-pth "norm", # llama-pth
"transformer.norm_f", # mpt dbrx "transformer.norm_f", # mpt dbrx
"ln_f", # refact bloom qwen gpt2 "ln_f", # refact bloom qwen gpt2
"language_model.encoder.final_layernorm", # persimmon
"model.final_layernorm", # persimmon "model.final_layernorm", # persimmon
"lm_head.ln", # phi2 "lm_head.ln", # phi2
"model.norm_f", # mamba-qbert "model.norm_f", # mamba-qbert
@@ -171,7 +168,6 @@ class TensorNameMap:
"transformer.h.{bid}.ln_mlp", # falcon40b "transformer.h.{bid}.ln_mlp", # falcon40b
"model.layers.{bid}.input_layernorm", # llama-hf nemotron olmoe phimoe granite-hybrid "model.layers.{bid}.input_layernorm", # llama-hf nemotron olmoe phimoe granite-hybrid
"layers.{bid}.attention_norm", # llama-pth "layers.{bid}.attention_norm", # llama-pth
"language_model.encoder.layers.{bid}.input_layernorm", # persimmon
"model.layers.{bid}.ln1", # yi "model.layers.{bid}.ln1", # yi
"h.{bid}.ln_1", # gpt2 "h.{bid}.ln_1", # gpt2
"transformer.h.{bid}.ln", # phi2 "transformer.h.{bid}.ln", # phi2
@@ -215,7 +211,6 @@ class TensorNameMap:
"transformer.blocks.{bid}.norm_attn_norm.attn.Wqkv", # dbrx "transformer.blocks.{bid}.norm_attn_norm.attn.Wqkv", # dbrx
"transformer.h.{bid}.self_attention.query_key_value", # falcon "transformer.h.{bid}.self_attention.query_key_value", # falcon
"h.{bid}.self_attention.query_key_value", # bloom "h.{bid}.self_attention.query_key_value", # bloom
"language_model.encoder.layers.{bid}.self_attention.query_key_value", # persimmon
"model.layers.{bid}.self_attn.query_key_value", # persimmon "model.layers.{bid}.self_attn.query_key_value", # persimmon
"model.layers.{bid}.attention.query_key_value", # bailingmoe2 "model.layers.{bid}.attention.query_key_value", # bailingmoe2
"h.{bid}.attn.c_attn", # gpt2 "h.{bid}.attn.c_attn", # gpt2
@@ -306,7 +301,6 @@ class TensorNameMap:
"layers.{bid}.attn.Wo", # modern-bert "layers.{bid}.attn.Wo", # modern-bert
"transformer.layer.{bid}.attention.out_lin", # distillbert "transformer.layer.{bid}.attention.out_lin", # distillbert
"transformer.h.{bid}.attn.out_proj", # gpt-j "transformer.h.{bid}.attn.out_proj", # gpt-j
"language_model.encoder.layers.{bid}.self_attention.dense", # persimmon
"model.layers.{bid}.self_attn.dense", # persimmon "model.layers.{bid}.self_attn.dense", # persimmon
"model.layers.{bid}.attention.dense", # bailingmoe2 "model.layers.{bid}.attention.dense", # bailingmoe2
"h.{bid}.attn.c_proj", # gpt2 "h.{bid}.attn.c_proj", # gpt2
@@ -373,7 +367,6 @@ class TensorNameMap:
"transformer.blocks.{bid}.norm_2", # mpt "transformer.blocks.{bid}.norm_2", # mpt
"model.layers.{bid}.post_attention_layernorm", # llama-hf nemotron olmoe phimoe "model.layers.{bid}.post_attention_layernorm", # llama-hf nemotron olmoe phimoe
"layers.{bid}.ffn_norm", # llama-pth "layers.{bid}.ffn_norm", # llama-pth
"language_model.encoder.layers.{bid}.post_attention_layernorm", # persimmon
"model.layers.{bid}.ln2", # yi "model.layers.{bid}.ln2", # yi
"h.{bid}.ln_2", # gpt2 "h.{bid}.ln_2", # gpt2
"model.layers.{bid}.ffn_norm", # internlm2 "model.layers.{bid}.ffn_norm", # internlm2
@@ -475,7 +468,6 @@ class TensorNameMap:
"transformer.layer.{bid}.ffn.lin1", # distillbert "transformer.layer.{bid}.ffn.lin1", # distillbert
"transformer.h.{bid}.mlp.fc_in", # gpt-j "transformer.h.{bid}.mlp.fc_in", # gpt-j
"transformer.h.{bid}.mlp.linear_3", # refact "transformer.h.{bid}.mlp.linear_3", # refact
"language_model.encoder.layers.{bid}.mlp.dense_h_to_4h", # persimmon
"model.layers.{bid}.mlp.dense_h_to_4h", # persimmon "model.layers.{bid}.mlp.dense_h_to_4h", # persimmon
"transformer.h.{bid}.mlp.w1", # qwen "transformer.h.{bid}.mlp.w1", # qwen
"h.{bid}.mlp.c_fc", # gpt2 "h.{bid}.mlp.c_fc", # gpt2
@@ -608,7 +600,6 @@ class TensorNameMap:
"layers.{bid}.mlp.Wo", # modern-bert "layers.{bid}.mlp.Wo", # modern-bert
"transformer.layer.{bid}.ffn.lin2", # distillbert "transformer.layer.{bid}.ffn.lin2", # distillbert
"transformer.h.{bid}.mlp.fc_out", # gpt-j "transformer.h.{bid}.mlp.fc_out", # gpt-j
"language_model.encoder.layers.{bid}.mlp.dense_4h_to_h", # persimmon
"model.layers.{bid}.mlp.dense_4h_to_h", # persimmon "model.layers.{bid}.mlp.dense_4h_to_h", # persimmon
"h.{bid}.mlp.c_proj", # gpt2 "h.{bid}.mlp.c_proj", # gpt2
"transformer.h.{bid}.mlp.fc2", # phi2 "transformer.h.{bid}.mlp.fc2", # phi2
@@ -663,7 +654,7 @@ class TensorNameMap:
), ),
MODEL_TENSOR.ATTN_Q_NORM: ( MODEL_TENSOR.ATTN_Q_NORM: (
"language_model.encoder.layers.{bid}.self_attention.q_layernorm", "encoder.layers.{bid}.self_attention.q_layernorm",
"model.layers.{bid}.self_attn.q_layernorm", # persimmon "model.layers.{bid}.self_attn.q_layernorm", # persimmon
"model.layers.{bid}.self_attn.query_layernorm", # hunyuan "model.layers.{bid}.self_attn.query_layernorm", # hunyuan
"model.layers.{bid}.attention.query_layernorm", # bailingmoe2 "model.layers.{bid}.attention.query_layernorm", # bailingmoe2
@@ -679,7 +670,7 @@ class TensorNameMap:
), ),
MODEL_TENSOR.ATTN_K_NORM: ( MODEL_TENSOR.ATTN_K_NORM: (
"language_model.encoder.layers.{bid}.self_attention.k_layernorm", "encoder.layers.{bid}.self_attention.k_layernorm",
"model.layers.{bid}.self_attn.k_layernorm", # persimmon "model.layers.{bid}.self_attn.k_layernorm", # persimmon
"model.layers.{bid}.self_attn.key_layernorm", # hunyuan "model.layers.{bid}.self_attn.key_layernorm", # hunyuan
"model.layers.{bid}.attention.key_layernorm", # bailingmoe2 "model.layers.{bid}.attention.key_layernorm", # bailingmoe2
@@ -695,7 +686,7 @@ class TensorNameMap:
), ),
MODEL_TENSOR.ROPE_FREQS: ( MODEL_TENSOR.ROPE_FREQS: (
"language_model.encoder.layers.{bid}.self_attention.rotary_emb.inv_freq", # persimmon "encoder.layers.{bid}.self_attention.rotary_emb.inv_freq", # persimmon
), ),
MODEL_TENSOR.LAYER_OUT_NORM: ( MODEL_TENSOR.LAYER_OUT_NORM: (