tqcq/llama.cpp
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Merge branch 'master' into cisc/jina-embeddings-v3

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Sigbjørn Skjæret
2025-06-01 19:34:17 +02:00
committed by GitHub
parent b17e9811f4 7675c555a1
commit 404670134e
231 changed files with 112390 additions and 9230 deletions
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92
gguf-py/gguf/constants.py
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@@ -177,6 +177,9 @@ class Keys:
EMBEDDING_LENGTH = "{arch}.convnext.embedding_length"
BLOCK_COUNT = "{arch}.convnext.block_count"
class Classifier:
OUTPUT_LABELS = "{arch}.classifier.output_labels"
class Tokenizer:
MODEL = "tokenizer.ggml.model"
PRE = "tokenizer.ggml.pre"
@@ -219,10 +222,13 @@ class Keys:
TYPE = "adapter.type"
LORA_ALPHA = "adapter.lora.alpha"
class ClipVision:
class Clip:
PROJECTOR_TYPE = "clip.projector_type"
HAS_VISION_ENCODER = "clip.has_vision_encoder"
HAS_AUDIO_ENCODER = "clip.has_audio_encoder"
HAS_LLAVA_PROJECTOR = "clip.has_llava_projector"
class ClipVision:
IMAGE_SIZE = "clip.vision.image_size"
PATCH_SIZE = "clip.vision.patch_size"
EMBEDDING_LENGTH = "clip.vision.embedding_length"
@@ -243,19 +249,33 @@ class Keys:
class Projector:
SCALE_FACTOR = "clip.vision.projector.scale_factor"
class ClipAudio:
NUM_MEL_BINS = "clip.audio.num_mel_bins"
EMBEDDING_LENGTH = "clip.audio.embedding_length"
FEED_FORWARD_LENGTH = "clip.audio.feed_forward_length"
PROJECTION_DIM = "clip.audio.projection_dim"
BLOCK_COUNT = "clip.audio.block_count"
class Attention:
HEAD_COUNT = "clip.audio.attention.head_count"
LAYERNORM_EPS = "clip.audio.attention.layer_norm_epsilon"
class Projector:
STACK_FACTOR = "clip.audio.projector.stack_factor"
#
# recommended mapping of model tensor names for storage in gguf
#
class GGUFType:
MODEL = "model"
ADAPTER = "adapter"
CLIP_VISION = "clip-vision"
MODEL = "model"
ADAPTER = "adapter"
MMPROJ = "mmproj" # dummy, unused for now
class MODEL_ARCH(IntEnum):
CLIP_VISION = auto() # dummy arch for clip.cpp
MMPROJ = auto() # dummy arch for clip.cpp
LLAMA = auto()
LLAMA4 = auto()
DECI = auto()
@@ -515,10 +535,28 @@ class MODEL_TENSOR(IntEnum):
V_RESMPL_QUERY = auto() # minicpmv
V_TOK_EMBD_IMG_BREAK = auto() # pixtral
V_MM_PATCH_MERGER = auto() # mistral small 3.1
# audio (mtmd)
A_ENC_EMBD_POS = auto()
A_ENC_CONV1D = auto()
A_PRE_NORM = auto()
A_POST_NORM = auto()
A_ENC_ATTN_Q = auto()
A_ENC_ATTN_K = auto()
A_ENC_ATTN_V = auto()
A_ENC_INPUT_NORM = auto()
A_ENC_OUTPUT = auto()
A_ENC_OUTPUT_NORM = auto()
A_ENC_FFN_UP = auto()
A_ENC_FFN_GATE = auto()
A_ENC_FFN_DOWN = auto()
A_MMPROJ = auto()
A_MMPROJ_FC = auto()
A_MM_NORM_PRE = auto()
A_MM_NORM_MID = auto()
MODEL_ARCH_NAMES: dict[MODEL_ARCH, str] = {
MODEL_ARCH.CLIP_VISION: "clip", # dummy arch for clip.cpp
MODEL_ARCH.MMPROJ: "clip", # dummy arch for clip.cpp
MODEL_ARCH.LLAMA: "llama",
MODEL_ARCH.LLAMA4: "llama4",
MODEL_ARCH.DECI: "deci",
@@ -778,10 +816,28 @@ TENSOR_NAMES: dict[MODEL_TENSOR, str] = {
MODEL_TENSOR.V_RESMPL_QUERY: "resampler.query",
MODEL_TENSOR.V_TOK_EMBD_IMG_BREAK: "v.token_embd.img_break", # pixtral
MODEL_TENSOR.V_MM_PATCH_MERGER: "mm.patch_merger", # mistral small 3.1
# audio (mtmd)
MODEL_TENSOR.A_ENC_EMBD_POS: "a.position_embd",
MODEL_TENSOR.A_ENC_CONV1D: "a.conv1d.{bid}",
MODEL_TENSOR.A_PRE_NORM: "a.pre_ln",
MODEL_TENSOR.A_POST_NORM: "a.post_ln",
MODEL_TENSOR.A_ENC_ATTN_Q: "a.blk.{bid}.attn_q",
MODEL_TENSOR.A_ENC_ATTN_K: "a.blk.{bid}.attn_k",
MODEL_TENSOR.A_ENC_ATTN_V: "a.blk.{bid}.attn_v",
MODEL_TENSOR.A_ENC_INPUT_NORM: "a.blk.{bid}.ln1",
MODEL_TENSOR.A_ENC_OUTPUT: "a.blk.{bid}.attn_out",
MODEL_TENSOR.A_ENC_OUTPUT_NORM: "a.blk.{bid}.ln2",
MODEL_TENSOR.A_ENC_FFN_UP: "a.blk.{bid}.ffn_up",
MODEL_TENSOR.A_ENC_FFN_GATE: "a.blk.{bid}.ffn_gate",
MODEL_TENSOR.A_ENC_FFN_DOWN: "a.blk.{bid}.ffn_down",
MODEL_TENSOR.A_MMPROJ: "mm.a.mlp.{bid}",
MODEL_TENSOR.A_MMPROJ_FC: "mm.a.fc",
MODEL_TENSOR.A_MM_NORM_PRE: "mm.a.norm_pre",
MODEL_TENSOR.A_MM_NORM_MID: "mm.a.norm_mid",
}
MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_ARCH.CLIP_VISION: [
MODEL_ARCH.MMPROJ: [
MODEL_TENSOR.V_MMPROJ,
MODEL_TENSOR.V_MMPROJ_FC,
MODEL_TENSOR.V_MMPROJ_MLP,
@@ -821,6 +877,24 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.V_RESMPL_QUERY,
MODEL_TENSOR.V_TOK_EMBD_IMG_BREAK,
MODEL_TENSOR.V_MM_PATCH_MERGER,
# audio
MODEL_TENSOR.A_ENC_EMBD_POS,
MODEL_TENSOR.A_ENC_CONV1D,
MODEL_TENSOR.A_PRE_NORM,
MODEL_TENSOR.A_POST_NORM,
MODEL_TENSOR.A_ENC_ATTN_Q,
MODEL_TENSOR.A_ENC_ATTN_K,
MODEL_TENSOR.A_ENC_ATTN_V,
MODEL_TENSOR.A_ENC_INPUT_NORM,
MODEL_TENSOR.A_ENC_OUTPUT,
MODEL_TENSOR.A_ENC_OUTPUT_NORM,
MODEL_TENSOR.A_ENC_FFN_UP,
MODEL_TENSOR.A_ENC_FFN_GATE,
MODEL_TENSOR.A_ENC_FFN_DOWN,
MODEL_TENSOR.A_MMPROJ,
MODEL_TENSOR.A_MMPROJ_FC,
MODEL_TENSOR.A_MM_NORM_PRE,
MODEL_TENSOR.A_MM_NORM_MID,
],
MODEL_ARCH.LLAMA: [
MODEL_TENSOR.TOKEN_EMBD,
@@ -964,6 +1038,7 @@ MODEL_TENSORS: dict[MODEL_ARCH, list[MODEL_TENSOR]] = {
MODEL_TENSOR.POS_EMBD,
MODEL_TENSOR.OUTPUT_NORM,
MODEL_TENSOR.ATTN_OUT_NORM,
MODEL_TENSOR.ATTN_QKV,
MODEL_TENSOR.ATTN_Q,
MODEL_TENSOR.ATTN_K,
MODEL_TENSOR.ATTN_V,
@@ -2200,7 +2275,10 @@ class VisionProjectorType:
LLAMA4 = "llama4"
QWEN2VL = "qwen2vl_merger"
QWEN25VL = "qwen2.5vl_merger"
ULTRAVOX = "ultravox"
INTERNVL = "internvl"
QWEN2A = "qwen2a" # audio
QWEN25O = "qwen2.5o" # omni
# Items here are (block size, type size)