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Merge branch 'master' into compilade/mamba2

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Francis Couture-Harpin
2025-05-01 17:43:53 -04:00
parent c9ecf620d6 b1dd4d08e8
commit 35d06fac5a
462 changed files with 75597 additions and 48146 deletions
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gguf-py/gguf/tensor_mapping.py
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@ -13,7 +13,7 @@ class TensorNameMap:
"transformer.wte", # gpt2 gpt-j mpt refact qwen dbrx jais exaone
"transformer.word_embeddings", # falcon
"word_embeddings", # bloom
"model.embed_tokens", # llama-hf nemotron olmoe olmo2 rwkv6qwen2
"model.embed_tokens", # llama-hf nemotron olmoe olmo2 rwkv6qwen2 glm4-0414
"tok_embeddings", # llama-pth
"embeddings.word_embeddings", # bert nomic-bert
"language_model.embedding.word_embeddings", # persimmon
@ -27,7 +27,10 @@ class TensorNameMap:
"embedding.word_embeddings", # chatglm
"transformer.token_embeddings", # openelm
"shared", # t5
"rwkv.embeddings", # rwkv
"rwkv.embeddings", # rwkv6
"model.embeddings", # rwkv7
"model.word_embeddings", # bailingmoe
"language_model.model.embed_tokens", # llama4
),
# Token type embeddings
@ -42,6 +45,9 @@ class TensorNameMap:
"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
),
@ -62,6 +68,7 @@ class TensorNameMap:
"output_layer", # chatglm
"head", # rwkv
"head.out", # wavtokenizer
"language_model.lm_head", # llama4
),
# Output norm
@ -81,8 +88,10 @@ class TensorNameMap:
"encoder.final_layernorm", # chatglm
"transformer.norm", # openelm
"model.norm", # nemotron
"rwkv.ln_out", # rwkv
"rwkv.ln_out", # rwkv6
"model.ln_out", # rwkv7
"backbone.final_layer_norm", # wavtokenizer
"language_model.model.norm", # llama4
),
# Rope frequencies
@ -122,14 +131,17 @@ class TensorNameMap:
"transformer.blocks.{bid}.norm_attn_norm.norm_1", # dbrx
"encoder.layers.{bid}.input_layernorm", # chatglm
"transformer.layers.{bid}.attn_norm", # openelm
"rwkv.blocks.{bid}.ln1", # rwkv
"rwkv.blocks.{bid}.ln1", # rwkv6
"model.layers.{bid}.ln1", # rwkv7
"language_model.model.layers.{bid}.input_layernorm", # llama4
),
# Attention norm 2
MODEL_TENSOR.ATTN_NORM_2: (
"transformer.h.{bid}.ln_attn", # falcon40b
"encoder.layer.{bid}.layer_norm_1", # jina-v2-code
"rwkv.blocks.{bid}.ln2", # rwkv
"rwkv.blocks.{bid}.ln2", # rwkv6
"model.layers.{bid}.ln2", # rwkv7
),
# Attention query-key-value
@ -161,6 +173,7 @@ class TensorNameMap:
"model.layers.{bid}.attention.wq", # internlm2
"transformer.decoder_layer.{bid}.multi_head_attention.query",# Grok
"transformer.h.{bid}.attn.attention.q_proj", # exaone
"language_model.model.layers.{bid}.self_attn.q_proj", # llama4
),
# Attention key
@ -175,6 +188,7 @@ class TensorNameMap:
"model.layers.{bid}.attention.wk", # internlm2
"transformer.decoder_layer.{bid}.multi_head_attention.key",# Grok
"transformer.h.{bid}.attn.attention.k_proj", # exaone
"language_model.model.layers.{bid}.self_attn.k_proj", # llama4
),
# Attention value
@ -188,6 +202,7 @@ class TensorNameMap:
"model.layers.{bid}.attention.wv", # internlm2
"transformer.decoder_layer.{bid}.multi_head_attention.value",# Grok
"transformer.h.{bid}.attn.attention.v_proj", # exaone
"language_model.model.layers.{bid}.self_attn.v_proj", # llama4
),
# Attention output
@ -214,6 +229,7 @@ class TensorNameMap:
"encoder.layers.{bid}.self_attention.dense", # chatglm
"transformer.layers.{bid}.attn.out_proj", # openelm
"transformer.h.{bid}.attn.attention.out_proj", # exaone
"language_model.model.layers.{bid}.self_attn.o_proj", # llama4
),
# Attention output norm
@ -225,7 +241,8 @@ class TensorNameMap:
),
MODEL_TENSOR.ATTN_POST_NORM: (
"model.layers.{bid}.post_attention_layernorm", # gemma2 olmo2
"model.layers.{bid}.post_attention_layernorm", # gemma2 olmo2 # ge
"model.layers.{bid}.post_self_attn_layernorm", # glm-4-0414
),
# Rotary embeddings
@ -251,6 +268,7 @@ class TensorNameMap:
"transformer.decoder_layer.{bid}.rms_norm_2", # Grok
"encoder.layers.{bid}.post_attention_layernorm", # chatglm
"transformer.layers.{bid}.ffn_norm", # openelm
"language_model.model.layers.{bid}.post_attention_layernorm", # llama4
),
# Post feed-forward norm
@ -261,6 +279,7 @@ class TensorNameMap:
# Post feed-forward norm
MODEL_TENSOR.FFN_POST_NORM: (
"model.layers.{bid}.post_feedforward_layernorm", # gemma2 olmo2
"model.layers.{bid}.post_mlp_layernorm", # glm-4-0414
),
MODEL_TENSOR.FFN_GATE_INP: (
@ -270,6 +289,8 @@ class TensorNameMap:
"transformer.decoder_layer.{bid}.router", # Grok
"transformer.blocks.{bid}.ffn.router.layer", # dbrx
"model.layers.{bid}.block_sparse_moe.router.layer", # granitemoe
"language_model.model.layers.{bid}.feed_forward.router", # llama4
"encoder.layers.{bid}.mlp.router.layer", # nomic-bert-moe
),
MODEL_TENSOR.FFN_GATE_INP_SHEXP: (
@ -298,15 +319,17 @@ class TensorNameMap:
"h.{bid}.mlp.c_fc", # gpt2
"transformer.h.{bid}.mlp.fc1", # phi2
"model.layers.{bid}.mlp.fc1", # phi2
"model.layers.{bid}.mlp.gate_up_proj", # phi3
"model.layers.{bid}.mlp.gate_up_proj", # phi3 glm-4-0414
"model.layers.layers.{bid}.mlp.up_proj", # plamo
"model.layers.{bid}.feed_forward.w3", # internlm2
"encoder.layers.{bid}.mlp.fc11", # nomic-bert
"encoder.layers.{bid}.mlp.fc1", # nomic-bert-moe
"model.layers.{bid}.mlp.c_fc", # starcoder2
"encoder.layer.{bid}.mlp.gated_layers_v", # jina-bert-v2
"model.layers.{bid}.residual_mlp.w3", # arctic
"encoder.layers.{bid}.mlp.dense_h_to_4h", # chatglm
"transformer.h.{bid}.mlp.c_fc_1", # exaone
"language_model.model.layers.{bid}.feed_forward.up_proj", # llama4
),
MODEL_TENSOR.FFN_UP_EXP: (
@ -315,11 +338,14 @@ class TensorNameMap:
"transformer.blocks.{bid}.ffn.experts.mlp.v1", # dbrx
"model.layers.{bid}.mlp.experts.up_proj", # qwen2moe olmoe (merged)
"model.layers.{bid}.block_sparse_moe.experts.w3", # phimoe (merged)
"language_model.model.layers.{bid}.feed_forward.experts.up_proj", # llama4
"encoder.layers.{bid}.mlp.experts.mlp.w1", # nomic-bert-moe
),
MODEL_TENSOR.FFN_UP_SHEXP: (
"model.layers.{bid}.mlp.shared_expert.up_proj", # qwen2moe
"model.layers.{bid}.mlp.shared_experts.up_proj", # deepseek deepseek2
"language_model.model.layers.{bid}.feed_forward.shared_expert.up_proj", # llama4
),
# AWQ-activation gate
@ -340,6 +366,7 @@ class TensorNameMap:
"transformer.h.{bid}.mlp.linear_1", # refact
"model.layers.{bid}.residual_mlp.w1", # arctic
"transformer.h.{bid}.mlp.c_fc_0", # exaone
"language_model.model.layers.{bid}.feed_forward.gate_proj", # llama4
),
MODEL_TENSOR.FFN_GATE_EXP: (
@ -348,11 +375,13 @@ class TensorNameMap:
"transformer.blocks.{bid}.ffn.experts.mlp.w1", # dbrx
"model.layers.{bid}.mlp.experts.gate_proj", # qwen2moe olmoe (merged)
"model.layers.{bid}.block_sparse_moe.experts.w1", # phimoe (merged)
"language_model.model.layers.{bid}.feed_forward.experts.gate_proj", # llama4
),
MODEL_TENSOR.FFN_GATE_SHEXP: (
"model.layers.{bid}.mlp.shared_expert.gate_proj", # qwen2moe
"model.layers.{bid}.mlp.shared_experts.gate_proj", # deepseek deepseek2
"language_model.model.layers.{bid}.feed_forward.shared_expert.gate_proj", # llama4
),
# Feed-forward down
@ -381,6 +410,7 @@ class TensorNameMap:
"encoder.layer.{bid}.mlp.down_layer", # jina-bert-v2
"encoder.layers.{bid}.mlp.dense_4h_to_h", # chatglm
"model.layers.h.{bid}.mlp.c_proj", # exaone
"language_model.model.layers.{bid}.feed_forward.down_proj", # llama4
),
MODEL_TENSOR.FFN_DOWN_EXP: (
@ -390,11 +420,14 @@ class TensorNameMap:
"model.layers.{bid}.mlp.experts.down_proj", # qwen2moe olmoe (merged)
"model.layers.{bid}.block_sparse_moe.output_linear", # granitemoe
"model.layers.{bid}.block_sparse_moe.experts.w2", # phimoe (merged)
"language_model.model.layers.{bid}.feed_forward.experts.down_proj", # llama4
"encoder.layers.{bid}.mlp.experts.mlp.w2", # nomic-bert-moe
),
MODEL_TENSOR.FFN_DOWN_SHEXP: (
"model.layers.{bid}.mlp.shared_expert.down_proj", # qwen2moe
"model.layers.{bid}.mlp.shared_experts.down_proj", # deepseek deepseek2
"language_model.model.layers.{bid}.feed_forward.shared_expert.down_proj", # llama4
),
MODEL_TENSOR.ATTN_Q_NORM: (
@ -466,112 +499,174 @@ class TensorNameMap:
"backbone.layers.{bid}.mixer.out_proj",
),
MODEL_TENSOR.TIME_MIX_W0: (
"model.layers.{bid}.attention.w0", # rwkv7
),
MODEL_TENSOR.TIME_MIX_W1: (
"rwkv.blocks.{bid}.attention.time_maa_w1", # rwkv v6
"model.layers.{bid}.self_attn.time_maa_w1", # rwkv6qwen2
"rwkv.blocks.{bid}.attention.time_maa_w1", # rwkv6
"model.layers.{bid}.self_attn.time_maa_w1", # rwkv6qwen2
"model.layers.{bid}.attention.w1", # rwkv7
),
MODEL_TENSOR.TIME_MIX_W2: (
"rwkv.blocks.{bid}.attention.time_maa_w2", # rwkv v6
"model.layers.{bid}.self_attn.time_maa_w2", # rwkv6qwen2
"rwkv.blocks.{bid}.attention.time_maa_w2", # rwkv6
"model.layers.{bid}.self_attn.time_maa_w2", # rwkv6qwen2
"model.layers.{bid}.attention.w2", # rwkv7
),
MODEL_TENSOR.TIME_MIX_A0: (
"model.layers.{bid}.attention.a0", # rwkv7
),
MODEL_TENSOR.TIME_MIX_A1: (
"model.layers.{bid}.attention.a1", # rwkv7
),
MODEL_TENSOR.TIME_MIX_A2: (
"model.layers.{bid}.attention.a2", # rwkv7
),
MODEL_TENSOR.TIME_MIX_V0: (
"model.layers.{bid}.attention.v0", # rwkv7
),
MODEL_TENSOR.TIME_MIX_V1: (
"model.layers.{bid}.attention.v1", # rwkv7
),
MODEL_TENSOR.TIME_MIX_V2: (
"model.layers.{bid}.attention.v2", # rwkv7
),
MODEL_TENSOR.TIME_MIX_G1: (
"model.layers.{bid}.attention.g1", # rwkv7
),
MODEL_TENSOR.TIME_MIX_G2: (
"model.layers.{bid}.attention.g2", # rwkv7
),
MODEL_TENSOR.TIME_MIX_K_K: (
"model.layers.{bid}.attention.k_k", # rwkv7
),
MODEL_TENSOR.TIME_MIX_K_A: (
"model.layers.{bid}.attention.k_a", # rwkv7
),
MODEL_TENSOR.TIME_MIX_R_K: (
"model.layers.{bid}.attention.r_k", # rwkv7
),
MODEL_TENSOR.TIME_MIX_LERP_X: (
"rwkv.blocks.{bid}.attention.time_maa_x", # rwkv v6
"rwkv.blocks.{bid}.attention.time_maa_x", # rwkv6
"model.layers.{bid}.self_attn.time_maa_x", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_LERP_K: (
"rwkv.blocks.{bid}.attention.time_maa_k", # rwkv v6
"rwkv.blocks.{bid}.attention.time_maa_k", # rwkv6
"model.layers.{bid}.self_attn.time_maa_k", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_LERP_V: (
"rwkv.blocks.{bid}.attention.time_maa_v", # rwkv v6
"rwkv.blocks.{bid}.attention.time_maa_v", # rwkv6
"model.layers.{bid}.self_attn.time_maa_v", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_LERP_R: (
"rwkv.blocks.{bid}.attention.time_maa_r", # rwkv v6
"rwkv.blocks.{bid}.attention.time_maa_r", # rwkv6
"model.layers.{bid}.self_attn.time_maa_r", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_LERP_G: (
"rwkv.blocks.{bid}.attention.time_maa_g", # rwkv v6
"rwkv.blocks.{bid}.attention.time_maa_g", # rwkv6
"model.layers.{bid}.self_attn.time_maa_g", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_LERP_W: (
"rwkv.blocks.{bid}.attention.time_maa_w", # rwkv v6
"rwkv.blocks.{bid}.attention.time_maa_w", # rwkv6
"model.layers.{bid}.self_attn.time_maa_w", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_FIRST: (
"rwkv.blocks.{bid}.attention.time_faaaa", # rwkv v6
"rwkv.blocks.{bid}.attention.time_faaaa", # rwkv6
),
MODEL_TENSOR.TIME_MIX_DECAY: (
"rwkv.blocks.{bid}.attention.time_decay", # rwkv v6
"rwkv.blocks.{bid}.attention.time_decay", # rwkv6
"model.layers.{bid}.self_attn.time_decay", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_DECAY_W1: (
"rwkv.blocks.{bid}.attention.time_decay_w1", # rwkv v6
"rwkv.blocks.{bid}.attention.time_decay_w1", # rwkv6
"model.layers.{bid}.self_attn.time_decay_w1", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_DECAY_W2: (
"rwkv.blocks.{bid}.attention.time_decay_w2", # rwkv v6
"rwkv.blocks.{bid}.attention.time_decay_w2", # rwkv6
"model.layers.{bid}.self_attn.time_decay_w2", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_KEY: (
"rwkv.blocks.{bid}.attention.key", # rwkv
"rwkv.blocks.{bid}.attention.key", # rwkv6
"model.layers.{bid}.self_attn.k_proj", # rwkv6qwen2
"model.layers.{bid}.attention.key", # rwkv7
"model.layers.{bid}.attention.k_proj", # rwkv7
),
MODEL_TENSOR.TIME_MIX_VALUE: (
"rwkv.blocks.{bid}.attention.value", # rwkv
"rwkv.blocks.{bid}.attention.value", # rwkv6
"model.layers.{bid}.self_attn.v_proj", # rwkv6qwen2
"model.layers.{bid}.attention.value", # rwkv7
"model.layers.{bid}.attention.v_proj", # rwkv7
),
MODEL_TENSOR.TIME_MIX_RECEPTANCE: (
"rwkv.blocks.{bid}.attention.receptance", # rwkv
"model.layers.{bid}.self_attn.q_proj", # rwkv6qwen2
"rwkv.blocks.{bid}.attention.receptance", # rwkv6
"model.layers.{bid}.self_attn.q_proj", # rwkv6qwen2
"model.layers.{bid}.attention.receptance", # rwkv7
"model.layers.{bid}.attention.r_proj", # rwkv7
),
MODEL_TENSOR.TIME_MIX_GATE: (
"rwkv.blocks.{bid}.attention.gate", # rwkv
"model.layers.{bid}.self_attn.gate", # rwkv6qwen2
"rwkv.blocks.{bid}.attention.gate", # rwkv6
"model.layers.{bid}.self_attn.gate", # rwkv6qwen2
),
MODEL_TENSOR.TIME_MIX_LN: (
"rwkv.blocks.{bid}.attention.ln_x", # rwkv
"rwkv.blocks.{bid}.attention.ln_x", # rwkv6
"model.layers.{bid}.attention.ln_x" # rwkv7
),
MODEL_TENSOR.TIME_MIX_OUTPUT: (
"rwkv.blocks.{bid}.attention.output", # rwkv
"rwkv.blocks.{bid}.attention.output", # rwkv6
"model.layers.{bid}.self_attn.o_proj", # rwkv6qwen2
"model.layers.{bid}.attention.output", # rwkv7
"model.layers.{bid}.attention.o_proj", # rwkv7
),
MODEL_TENSOR.CHANNEL_MIX_LERP_K: (
"rwkv.blocks.{bid}.feed_forward.time_maa_k", # rwkv v6
"rwkv.blocks.{bid}.feed_forward.time_maa_k", # rwkv6
"model.layers.{bid}.feed_forward.x_k", # rwkv7
),
MODEL_TENSOR.CHANNEL_MIX_LERP_R: (
"rwkv.blocks.{bid}.feed_forward.time_maa_r", # rwkv v6
"rwkv.blocks.{bid}.feed_forward.time_maa_r", # rwkv6
),
MODEL_TENSOR.CHANNEL_MIX_KEY: (
"rwkv.blocks.{bid}.feed_forward.key", # rwkv
"rwkv.blocks.{bid}.feed_forward.key", # rwkv6
"model.layers.{bid}.feed_forward.key", # rwkv7
),
MODEL_TENSOR.CHANNEL_MIX_RECEPTANCE: (
"rwkv.blocks.{bid}.feed_forward.receptance", # rwkv
"rwkv.blocks.{bid}.feed_forward.receptance", # rwkv6
),
MODEL_TENSOR.CHANNEL_MIX_VALUE: (
"rwkv.blocks.{bid}.feed_forward.value", # rwkv
"rwkv.blocks.{bid}.feed_forward.value", # rwkv6
"model.layers.{bid}.feed_forward.value", # rwkv7
),
MODEL_TENSOR.ATTN_Q_A: (
@ -590,6 +685,14 @@ class TensorNameMap:
"model.layers.{bid}.self_attn.kv_b_proj", # deepseek2
),
MODEL_TENSOR.ATTN_K_B: (
"model.layers.{bid}.self_attn.k_b_proj", # deepseek2
),
MODEL_TENSOR.ATTN_V_B: (
"model.layers.{bid}.self_attn.v_b_proj", # deepseek2
),
MODEL_TENSOR.ATTN_Q_A_NORM: (
"model.layers.{bid}.self_attn.q_a_layernorm", # deepseek2
),
@ -791,6 +894,176 @@ class TensorNameMap:
MODEL_TENSOR.POSNET_ATTN_OUT: (
"backbone.posnet.{bid}.proj_out", # wavtokenizer
),
#############################################################################
## Vision encoder
MODEL_TENSOR.V_MMPROJ: (
"multi_modal_projector.linear_{bid}",
),
MODEL_TENSOR.V_MMPROJ_FC: (
"model.connector.modality_projection.proj", # SmolVLM
),
MODEL_TENSOR.V_MMPROJ_MLP: (
"model.mm_projector.mlp.mlp.{bid}",
),
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_TENSOR.V_ENC_EMBD_PATCH: (
"vision_tower.vision_model.embeddings.patch_embedding",
"vpm.embeddings.patch_embedding",
"model.vision_model.embeddings.patch_embedding", # SmolVLM
"vision_tower.patch_conv", # pixtral
),
MODEL_TENSOR.V_ENC_EMBD_POS: (
"vision_tower.vision_model.embeddings.position_embedding",
"vpm.embeddings.position_embedding",
"model.vision_model.embeddings.position_embedding", # SmolVLM
),
MODEL_TENSOR.V_ENC_ATTN_Q: (
"vision_tower.vision_model.encoder.layers.{bid}.self_attn.q_proj",
"vpm.encoder.layers.{bid}.self_attn.q_proj",
"model.vision_model.encoder.layers.{bid}.self_attn.q_proj", # SmolVLM
"vision_tower.transformer.layers.{bid}.attention.q_proj", # pixtral
),
MODEL_TENSOR.V_ENC_ATTN_K: (
"vision_tower.vision_model.encoder.layers.{bid}.self_attn.k_proj",
"vpm.encoder.layers.{bid}.self_attn.k_proj",
"model.vision_model.encoder.layers.{bid}.self_attn.k_proj", # SmolVLM
"vision_tower.transformer.layers.{bid}.attention.k_proj", # pixtral
),
MODEL_TENSOR.V_ENC_ATTN_V: (
"vision_tower.vision_model.encoder.layers.{bid}.self_attn.v_proj",
"vpm.encoder.layers.{bid}.self_attn.v_proj",
"model.vision_model.encoder.layers.{bid}.self_attn.v_proj", # SmolVLM
"vision_tower.transformer.layers.{bid}.attention.v_proj", # pixtral
),
MODEL_TENSOR.V_ENC_INPUT_NORM: (
"vision_tower.vision_model.encoder.layers.{bid}.layer_norm1",
"vpm.encoder.layers.{bid}.layer_norm1",
"model.vision_model.encoder.layers.{bid}.layer_norm1", # SmolVLM
"vision_tower.transformer.layers.{bid}.attention_norm", # pixtral
),
MODEL_TENSOR.V_ENC_OUTPUT: (
"vision_tower.vision_model.encoder.layers.{bid}.self_attn.out_proj",
"vpm.encoder.layers.{bid}.self_attn.out_proj",
"model.vision_model.encoder.layers.{bid}.self_attn.out_proj", # SmolVLM
"vision_tower.transformer.layers.{bid}.attention.o_proj", # pixtral
),
MODEL_TENSOR.V_ENC_OUTPUT_NORM: (
"vision_tower.vision_model.encoder.layers.{bid}.layer_norm2",
"vpm.encoder.layers.{bid}.layer_norm2",
"model.vision_model.encoder.layers.{bid}.layer_norm2", # SmolVLM
"vision_tower.transformer.layers.{bid}.ffn_norm", # pixtral
),
MODEL_TENSOR.V_ENC_FFN_UP: (
"vision_tower.vision_model.encoder.layers.{bid}.mlp.fc1",
"vpm.encoder.layers.{bid}.mlp.fc1",
"model.vision_model.encoder.layers.{bid}.mlp.fc2", # SmolVLM, gemma3 (note: name is swapped)
"vision_tower.transformer.layers.{bid}.feed_forward.up_proj", # pixtral
),
MODEL_TENSOR.V_ENC_FFN_GATE: (
"vision_tower.transformer.layers.{bid}.feed_forward.gate_proj", # pixtral
),
MODEL_TENSOR.V_ENC_FFN_DOWN: (
"vision_tower.vision_model.encoder.layers.{bid}.mlp.fc2",
"vpm.encoder.layers.{bid}.mlp.fc2",
"model.vision_model.encoder.layers.{bid}.mlp.fc1", # SmolVLM, gemma3 (note: name is swapped)
"vision_tower.transformer.layers.{bid}.feed_forward.down_proj", # pixtral
),
MODEL_TENSOR.V_PRE_NORM: (
"vision_tower.vision_model.pre_layrnorm",
"vision_tower.ln_pre", # pixtral
),
MODEL_TENSOR.V_POST_NORM: (
"vision_tower.vision_model.post_layernorm",
"model.vision_model.post_layernorm", # SmolVLM
),
MODEL_TENSOR.V_MM_INP_PROJ: (
"multi_modal_projector.mm_input_projection",
),
MODEL_TENSOR.V_MM_INP_NORM: (
"multi_modal_projector.norm",
),
MODEL_TENSOR.V_MM_SOFT_EMB_NORM: (
"multi_modal_projector.mm_soft_emb_norm",
),
MODEL_TENSOR.V_RESMPL_POS_EMBD_K: (
"resampler.pos_embed_k",
),
MODEL_TENSOR.V_RESMPL_ATTN_Q: (
"resampler.attn.in_proj_q", # tensor generated from resampler.attn.in_proj
),
MODEL_TENSOR.V_RESMPL_ATTN_K: (
"resampler.attn.in_proj_k", # tensor generated from resampler.attn.in_proj
),
MODEL_TENSOR.V_RESMPL_ATTN_V: (
"resampler.attn.in_proj_v", # tensor generated from resampler.attn.in_proj
),
MODEL_TENSOR.V_RESMPL_ATTN_OUT: (
"resampler.attn.out_proj",
),
MODEL_TENSOR.V_RESMPL_KV: (
"resampler.kv_proj",
),
MODEL_TENSOR.V_RESMPL_POST_NORM: (
"resampler.ln_post",
),
MODEL_TENSOR.V_RESMPL_KV_NORM: (
"resampler.ln_kv",
),
MODEL_TENSOR.V_RESMPL_Q_NORM: (
"resampler.ln_q",
),
MODEL_TENSOR.V_RESMPL_PROJ: (
"resampler.proj",
),
MODEL_TENSOR.V_RESMPL_QUERY: (
"resampler.query",
),
MODEL_TENSOR.V_TOK_EMBD_IMG_BREAK: (
"v.token_embd.img_break", # for pixtral, this is a generated vector
),
MODEL_TENSOR.V_MM_PATCH_MERGER: (
"multi_modal_projector.patch_merger.merging_layer", # mistral small 3.1
),
}
# architecture-specific block mappings