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Merged
dxqb merged 20 commits into from
Nov 27, 2025
Merged

Quantization layer filter #1091

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eaf4fe2
make layer filter a component
dxqb Nov 2, 2025
867b84c
quantization layer filter
dxqb Nov 2, 2025
e5d0317
add blocks preset
dxqb Nov 2, 2025
1f45c04
Merge branch 'blocks' into quant_layer_filter
dxqb Nov 2, 2025
0242d16
quantization filter in presets
dxqb Nov 2, 2025
3448801
bugfix
dxqb Nov 2, 2025
27dc59d
merge
dxqb Nov 14, 2025
69f0fa1
merge fix
dxqb Nov 14, 2025
1739bfe
Fixes [Bug]: Layer filter isn't configured correct if a preset is loaded
O-J1 Nov 16, 2025
968b2a9
Simplify tooltip text for layer filter
dxqb Nov 16, 2025
6f2d2f5
Tweak tooltip text a little more
O-J1 Nov 16, 2025
ea29f8f
Merge branch 'upstream' into quant_layer_filter
dxqb Nov 16, 2025
1a7c5a6
initial
dxqb Nov 16, 2025
606b7a8
merge with #1139
dxqb Nov 22, 2025
8ce4604
merge with upstream
dxqb Nov 22, 2025
50982b7
UI update
dxqb Nov 22, 2025
16a6015
UI update
dxqb Nov 22, 2025
b9bf5b4
fix comment
dxqb Nov 22, 2025
355f522
merge #1143
dxqb Nov 24, 2025
a5a3550
Merge branch 'merge' into quant_layer_filter
dxqb Nov 27, 2025
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4 changes: 3 additions & 1 deletion modules/modelLoader/GenericEmbeddingModelLoader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes
from modules.util.ModuleFilter import ModuleFilter


def make_embedding_model_loader(
Expand Down Expand Up @@ -32,6 +33,7 @@ def load(
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
quant_filters: list[ModuleFilter] | None = None,
) -> model_class | None:
base_model_loader = model_loader_class()
embedding_loader = embedding_loader_class()
Expand All @@ -41,7 +43,7 @@ def load(
model.model_spec = self._load_default_model_spec(model_type)

if model_names.base_model is not None:
base_model_loader.load(model, model_type, model_names, weight_dtypes)
base_model_loader.load(model, model_type, model_names, weight_dtypes, quant_filters)
embedding_loader.load(model, model_names.embedding.model_name, model_names)

return model
Expand Down
4 changes: 3 additions & 1 deletion modules/modelLoader/GenericFineTuneModelLoader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes
from modules.util.ModuleFilter import ModuleFilter


def make_fine_tune_model_loader(
Expand Down Expand Up @@ -32,6 +33,7 @@ def load(
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
quant_filters: list[ModuleFilter] | None = None,
) -> model_class | None:
base_model_loader = model_loader_class()
if embedding_loader_class is not None:
Expand All @@ -42,7 +44,7 @@ def load(
self._load_internal_data(model, model_names.base_model)
model.model_spec = self._load_default_model_spec(model_type)

base_model_loader.load(model, model_type, model_names, weight_dtypes)
base_model_loader.load(model, model_type, model_names, weight_dtypes, quant_filters)
if embedding_loader_class is not None:
embedding_loader.load(model, model_names.base_model, model_names)

Expand Down
4 changes: 3 additions & 1 deletion modules/modelLoader/GenericLoRAModelLoader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,6 +5,7 @@
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes
from modules.util.ModuleFilter import ModuleFilter


def make_lora_model_loader(
Expand Down Expand Up @@ -33,6 +34,7 @@ def load(
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
quant_filters: list[ModuleFilter] | None = None,
) -> model_class | None:
base_model_loader = model_loader_class()
lora_model_loader = lora_loader_class()
Expand All @@ -44,7 +46,7 @@ def load(
model.model_spec = self._load_default_model_spec(model_type)

if model_names.base_model is not None:
base_model_loader.load(model, model_type, model_names, weight_dtypes)
base_model_loader.load(model, model_type, model_names, weight_dtypes, quant_filters)
lora_model_loader.load(model, model_names)
if embedding_loader_class is not None:
embedding_loader.load(model, model_names.lora, model_names)
Expand Down
16 changes: 11 additions & 5 deletions modules/modelLoader/chroma/ChromaModelLoader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes
from modules.util.ModuleFilter import ModuleFilter

import torch

Expand All @@ -33,10 +34,11 @@ def __load_internal(
base_model_name: str,
transformer_model_name: str,
vae_model_name: str,
quant_filters: list[ModuleFilter],
):
if os.path.isfile(os.path.join(base_model_name, "meta.json")):
self.__load_diffusers(
model, model_type, weight_dtypes, base_model_name, transformer_model_name, vae_model_name,
model, model_type, weight_dtypes, base_model_name, transformer_model_name, vae_model_name, quant_filters,
)
else:
raise Exception("not an internal model")
Expand All @@ -49,6 +51,7 @@ def __load_diffusers(
base_model_name: str,
transformer_model_name: str,
vae_model_name: str,
quant_filters: list[ModuleFilter],
):
diffusers_sub = []
if not transformer_model_name:
Expand Down Expand Up @@ -104,7 +107,7 @@ def __load_diffusers(
quantization_config=GGUFQuantizationConfig(compute_dtype=torch.bfloat16) if weight_dtypes.transformer == DataType.GGUF else None,
)
transformer = self._convert_diffusers_sub_module_to_dtype(
transformer, weight_dtypes.transformer, weight_dtypes.train_dtype
transformer, weight_dtypes.transformer, weight_dtypes.train_dtype, quant_filters,
)
else:
transformer = self._load_diffusers_sub_module(
Expand All @@ -113,6 +116,7 @@ def __load_diffusers(
weight_dtypes.train_dtype,
base_model_name,
"transformer",
quant_filters,
)

model.model_type = model_type
Expand All @@ -130,6 +134,7 @@ def __load_safetensors(
base_model_name: str,
transformer_model_name: str,
vae_model_name: str,
quant_filters: list[ModuleFilter],
):
#no single file .safetensors for Chroma available at the time of writing this code
raise NotImplementedError("Loading of single file Chroma models not supported. Use the diffusers model instead. Optionally, transformer-only safetensor files can be loaded by overriding the transformer.")
Expand All @@ -140,28 +145,29 @@ def load(
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
quant_filters: list[ModuleFilter] | None = None,
):
stacktraces = []

try:
self.__load_internal(
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model,
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model, quant_filters,
)
return
except Exception:
stacktraces.append(traceback.format_exc())

try:
self.__load_diffusers(
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model,
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model, quant_filters,
)
return
except Exception:
stacktraces.append(traceback.format_exc())

try:
self.__load_safetensors(
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model,
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model, quant_filters,
)
return
except Exception:
Expand Down
18 changes: 12 additions & 6 deletions modules/modelLoader/flux/FluxModelLoader.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes
from modules.util.ModuleFilter import ModuleFilter

import torch

Expand Down Expand Up @@ -36,11 +37,12 @@ def __load_internal(
vae_model_name: str,
include_text_encoder_1: bool,
include_text_encoder_2: bool,
quant_filters: list[ModuleFilter],
):
if os.path.isfile(os.path.join(base_model_name, "meta.json")):
self.__load_diffusers(
model, model_type, weight_dtypes, base_model_name, transformer_model_name, vae_model_name,
include_text_encoder_1, include_text_encoder_2,
include_text_encoder_1, include_text_encoder_2, quant_filters,
)
else:
raise Exception("not an internal model")
Expand All @@ -55,6 +57,7 @@ def __load_diffusers(
vae_model_name: str,
include_text_encoder_1: bool,
include_text_encoder_2: bool,
quant_filters: list[ModuleFilter],
):
diffusers_sub = []
transformers_sub = []
Expand Down Expand Up @@ -140,7 +143,7 @@ def __load_diffusers(
quantization_config=GGUFQuantizationConfig(compute_dtype=torch.bfloat16) if weight_dtypes.transformer == DataType.GGUF else None,
)
transformer = self._convert_diffusers_sub_module_to_dtype(
transformer, weight_dtypes.transformer, weight_dtypes.train_dtype
transformer, weight_dtypes.transformer, weight_dtypes.train_dtype, quant_filters,
)
else:
transformer = self._load_diffusers_sub_module(
Expand All @@ -149,6 +152,7 @@ def __load_diffusers(
weight_dtypes.train_dtype,
base_model_name,
"transformer",
quant_filters,
)

model.model_type = model_type
Expand All @@ -170,6 +174,7 @@ def __load_safetensors(
vae_model_name: str,
include_text_encoder_1: bool,
include_text_encoder_2: bool,
quant_filters: list[ModuleFilter],
):
transformer = FluxTransformer2DModel.from_single_file(
#always load transformer separately even though FluxPipeLine.from_single_file() could load it, to avoid loading in float32:
Expand Down Expand Up @@ -222,7 +227,7 @@ def __load_safetensors(
print("text encoder 2 (t5) not loaded, continuing without it")

transformer = self._convert_diffusers_sub_module_to_dtype(
pipeline.transformer, weight_dtypes.transformer, weight_dtypes.train_dtype
pipeline.transformer, weight_dtypes.transformer, weight_dtypes.train_dtype, quant_filters,
)

model.model_type = model_type
Expand All @@ -240,13 +245,14 @@ def load(
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
quant_filters: list[ModuleFilter] | None = None,
):
stacktraces = []

try:
self.__load_internal(
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model,
model_names.include_text_encoder, model_names.include_text_encoder_2,
model_names.include_text_encoder, model_names.include_text_encoder_2, quant_filters,
)
return
except Exception:
Expand All @@ -255,7 +261,7 @@ def load(
try:
self.__load_diffusers(
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model,
model_names.include_text_encoder, model_names.include_text_encoder_2,
model_names.include_text_encoder, model_names.include_text_encoder_2, quant_filters,
)
return
except Exception:
Expand All @@ -264,7 +270,7 @@ def load(
try:
self.__load_safetensors(
model, model_type, weight_dtypes, model_names.base_model, model_names.transformer_model, model_names.vae_model,
model_names.include_text_encoder, model_names.include_text_encoder_2,
model_names.include_text_encoder, model_names.include_text_encoder_2, quant_filters,
)
return
except Exception:
Expand Down
16 changes: 11 additions & 5 deletions modules/modelLoader/hiDream/HiDreamModelLoader.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,7 @@
from modules.util.enum.ModelType import ModelType
from modules.util.ModelNames import ModelNames
from modules.util.ModelWeightDtypes import ModelWeightDtypes
from modules.util.ModuleFilter import ModuleFilter

from diffusers import (
AutoencoderKL,
Expand Down Expand Up @@ -42,11 +43,12 @@ def __load_internal(
include_text_encoder_2: bool,
include_text_encoder_3: bool,
include_text_encoder_4: bool,
quant_filters: list[ModuleFilter],
):
if os.path.isfile(os.path.join(base_model_name, "meta.json")):
self.__load_diffusers(
model, model_type, weight_dtypes, base_model_name, text_encoder_4_model_name, vae_model_name,
include_text_encoder_1, include_text_encoder_2, include_text_encoder_3, include_text_encoder_4,
include_text_encoder_1, include_text_encoder_2, include_text_encoder_3, include_text_encoder_4, quant_filters,
)
else:
raise Exception("not an internal model")
Expand All @@ -63,6 +65,7 @@ def __load_diffusers(
include_text_encoder_2: bool,
include_text_encoder_3: bool,
include_text_encoder_4: bool,
quant_filters: list[ModuleFilter],
):
diffusers_sub = []
transformers_sub = []
Expand Down Expand Up @@ -191,6 +194,7 @@ def __load_diffusers(
weight_dtypes.train_dtype,
base_model_name,
"transformer",
quant_filters,
)

model.model_type = model_type
Expand Down Expand Up @@ -218,6 +222,7 @@ def __load_safetensors(
include_text_encoder_2: bool,
include_text_encoder_3: bool,
include_text_encoder_4: bool,
quant_filters: list[ModuleFilter],
):
pipeline = HiDreamImagePipeline.from_single_file(
pretrained_model_link_or_path=base_model_name,
Expand Down Expand Up @@ -264,7 +269,7 @@ def __load_safetensors(
print("text encoder 2 (t5) not loaded, continuing without it")

transformer = self._convert_diffusers_sub_module_to_dtype(
pipeline.transformer, weight_dtypes.transformer, weight_dtypes.train_dtype
pipeline.transformer, weight_dtypes.transformer, weight_dtypes.train_dtype, quant_filters,
)

model.model_type = model_type
Expand All @@ -290,6 +295,7 @@ def load(
model_type: ModelType,
model_names: ModelNames,
weight_dtypes: ModelWeightDtypes,
quant_filters: list[ModuleFilter] | None = None,
):
stacktraces = []

Expand All @@ -298,7 +304,7 @@ def load(
model, model_type, weight_dtypes, model_names.base_model,
model_names.text_encoder_4, model_names.vae_model,
model_names.include_text_encoder, model_names.include_text_encoder_2,
model_names.include_text_encoder_3, model_names.include_text_encoder_4,
model_names.include_text_encoder_3, model_names.include_text_encoder_4, quant_filters,
)
self.__after_load(model)
return
Expand All @@ -310,7 +316,7 @@ def load(
model, model_type, weight_dtypes, model_names.base_model,
model_names.text_encoder_4, model_names.vae_model,
model_names.include_text_encoder, model_names.include_text_encoder_2,
model_names.include_text_encoder_3, model_names.include_text_encoder_4,
model_names.include_text_encoder_3, model_names.include_text_encoder_4, quant_filters,
)
self.__after_load(model)
return
Expand All @@ -322,7 +328,7 @@ def load(
model, model_type, weight_dtypes, model_names.base_model,
model_names.text_encoder_4, model_names.vae_model,
model_names.include_text_encoder, model_names.include_text_encoder_2,
model_names.include_text_encoder_3, model_names.include_text_encoder_4,
model_names.include_text_encoder_3, model_names.include_text_encoder_4, quant_filters,
)
self.__after_load(model)
return
Expand Down
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