use shared.hf_endpoin

Author: w-e-w

modules/dat_model.py

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

modules/models/sd3/sd3_cond.py

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

modules/sd_disable_initialization.py

@@ -76,7 +76,7 @@ def transformers_modeling_utils_load_pretrained_model(*args, **kwargs):
         def transformers_utils_hub_get_file_from_cache(original, url, *args, **kwargs):
 
             # this file is always 404, prevent making request
-            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':
+            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':
                 return None
 
             try: