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Merge 8a09e9f209959f923bbf8917afec9a99a89e065f into 374bb6cc384d2a19422c0b07d69de0a41d1f3f4d

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licyk 2025-03-22 08:23:09 +00:00 committed by GitHub
commit b24ca2ed03
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6 changed files with 11 additions and 10 deletions
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8
modules/dat_model.py
View File

@ -1,7 +1,7 @@
import os import os
from modules import modelloader, errors from modules import modelloader, errors
from modules.shared import cmd_opts, opts, hf_endpoint from modules.shared import cmd_opts, opts
from modules.upscaler import Upscaler, UpscalerData from modules.upscaler import Upscaler, UpscalerData
from modules.upscaler_utils import upscale_with_model from modules.upscaler_utils import upscale_with_model
@ -71,21 +71,21 @@ def get_dat_models(scaler):
return [ return [
UpscalerData( UpscalerData(
name="DAT x2", name="DAT x2",
path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x2.pth", path="https://huggingface.co/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x2.pth",
scale=2, scale=2,
upscaler=scaler, upscaler=scaler,
sha256='7760aa96e4ee77e29d4f89c3a4486200042e019461fdb8aa286f49aa00b89b51', sha256='7760aa96e4ee77e29d4f89c3a4486200042e019461fdb8aa286f49aa00b89b51',
), ),
UpscalerData( UpscalerData(
name="DAT x3", name="DAT x3",
path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x3.pth", path="https://huggingface.co/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x3.pth",
scale=3, scale=3,
upscaler=scaler, upscaler=scaler,
sha256='581973e02c06f90d4eb90acf743ec9604f56f3c2c6f9e1e2c2b38ded1f80d197', sha256='581973e02c06f90d4eb90acf743ec9604f56f3c2c6f9e1e2c2b38ded1f80d197',
), ),
UpscalerData( UpscalerData(
name="DAT x4", name="DAT x4",
path=f"{hf_endpoint}/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x4.pth", path="https://huggingface.co/w-e-w/DAT/resolve/main/experiments/pretrained_models/DAT/DAT_x4.pth",
scale=4, scale=4,
upscaler=scaler, upscaler=scaler,
sha256='391a6ce69899dff5ea3214557e9d585608254579217169faf3d4c353caff049e', sha256='391a6ce69899dff5ea3214557e9d585608254579217169faf3d4c353caff049e',

6
modules/models/sd3/sd3_cond.py
View File

@ -24,7 +24,7 @@ class SafetensorsMapping(typing.Mapping):
return self.file.get_tensor(key) return self.file.get_tensor(key)
CLIPL_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_l.safetensors" CLIPL_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_l.safetensors"
CLIPL_CONFIG = { CLIPL_CONFIG = {
"hidden_act": "quick_gelu", "hidden_act": "quick_gelu",
"hidden_size": 768, "hidden_size": 768,
@ -33,7 +33,7 @@ CLIPL_CONFIG = {
"num_hidden_layers": 12, "num_hidden_layers": 12,
} }
CLIPG_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_g.safetensors" CLIPG_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/clip_g.safetensors"
CLIPG_CONFIG = { CLIPG_CONFIG = {
"hidden_act": "gelu", "hidden_act": "gelu",
"hidden_size": 1280, "hidden_size": 1280,
@ -43,7 +43,7 @@ CLIPG_CONFIG = {
"textual_inversion_key": "clip_g", "textual_inversion_key": "clip_g",
} }
T5_URL = f"{shared.hf_endpoint}/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/t5xxl_fp16.safetensors" T5_URL = "https://huggingface.co/AUTOMATIC/stable-diffusion-3-medium-text-encoders/resolve/main/t5xxl_fp16.safetensors"
T5_CONFIG = { T5_CONFIG = {
"d_ff": 10240, "d_ff": 10240,
"d_model": 4096, "d_model": 4096,

2
modules/sd_disable_initialization.py
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@ -76,7 +76,7 @@ class DisableInitialization(ReplaceHelper):
def transformers_utils_hub_get_file_from_cache(original, url, *args, **kwargs): def transformers_utils_hub_get_file_from_cache(original, url, *args, **kwargs):
# this file is always 404, prevent making request # this file is always 404, prevent making request
if url == f'{shared.hf_endpoint}/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json': if url == 'https://huggingface.co/openai/clip-vit-large-patch14/resolve/main/added_tokens.json' or url == 'openai/clip-vit-large-patch14' and args[0] == 'added_tokens.json':
return None return None
try: try:

2
modules/sd_models.py
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@ -160,7 +160,7 @@ def list_models():
model_url = None model_url = None
expected_sha256 = None expected_sha256 = None
else: else:
model_url = f"{shared.hf_endpoint}/stable-diffusion-v1-5/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors" model_url = "https://huggingface.co/stable-diffusion-v1-5/stable-diffusion-v1-5/resolve/main/v1-5-pruned-emaonly.safetensors"
expected_sha256 = '6ce0161689b3853acaa03779ec93eafe75a02f4ced659bee03f50797806fa2fa' expected_sha256 = '6ce0161689b3853acaa03779ec93eafe75a02f4ced659bee03f50797806fa2fa'
model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt", ".safetensors"], download_name="v1-5-pruned-emaonly.safetensors", ext_blacklist=[".vae.ckpt", ".vae.safetensors"], hash_prefix=expected_sha256) model_list = modelloader.load_models(model_path=model_path, model_url=model_url, command_path=shared.cmd_opts.ckpt_dir, ext_filter=[".ckpt", ".safetensors"], download_name="v1-5-pruned-emaonly.safetensors", ext_blacklist=[".vae.ckpt", ".vae.safetensors"], hash_prefix=expected_sha256)

2
modules/shared.py
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@ -91,4 +91,4 @@ refresh_checkpoints = shared_items.refresh_checkpoints
list_samplers = shared_items.list_samplers list_samplers = shared_items.list_samplers
reload_hypernetworks = shared_items.reload_hypernetworks reload_hypernetworks = shared_items.reload_hypernetworks
hf_endpoint = os.getenv('HF_ENDPOINT', 'https://huggingface.co') hf_endpoint = os.getenv('HF_ENDPOINT', 'https://huggingface.co').rstrip('/')

1
modules/util.py
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@ -254,6 +254,7 @@ def load_file_from_url(
parts = urlparse(url) parts = urlparse(url)
file_name = os.path.basename(parts.path) file_name = os.path.basename(parts.path)
url = str.replace(url, "https://huggingface.co", shared.hf_endpoint, 1)
cached_file = os.path.abspath(os.path.join(model_dir, file_name)) cached_file = os.path.abspath(os.path.join(model_dir, file_name))
if re_download or not os.path.exists(cached_file): if re_download or not os.path.exists(cached_file):