Update app.py

app.py

@@ -13,25 +13,25 @@ DESCRIPTION = """
 Demo for the WaifuDiffusion tagger models
 """
 
-HF_TOKEN1 = os.environ.get("HF_TOKEN1", "")
+HF_TOKEN = os.environ.get("HF_TOKEN", "")
 
 # Dataset v3 series of models:
-SWINV2_MODEL_DSV3_REPO = "SmilingWolf/wd-swinv2-tagger-v3"
-CONV_MODEL_DSV3_REPO = "SmilingWolf/wd-convnext-tagger-v3"
+# SWINV2_MODEL_DSV3_REPO = "SmilingWolf/wd-swinv2-tagger-v3"
+# CONV_MODEL_DSV3_REPO = "SmilingWolf/wd-convnext-tagger-v3"
 VIT_MODEL_DSV3_REPO = "ura23/wd-vit-tagger-v3"
-VIT_LARGE_MODEL_DSV3_REPO = "SmilingWolf/wd-vit-large-tagger-v3"
-EVA02_LARGE_MODEL_DSV3_REPO = "SmilingWolf/wd-eva02-large-tagger-v3"
+# VIT_LARGE_MODEL_DSV3_REPO = "SmilingWolf/wd-vit-large-tagger-v3"
+# EVA02_LARGE_MODEL_DSV3_REPO = "SmilingWolf/wd-eva02-large-tagger-v3"
 
 # Dataset v2 series of models:
-MOAT_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-moat-tagger-v2"
-SWIN_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-swinv2-tagger-v2"
-CONV_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-convnext-tagger-v2"
-CONV2_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-convnextv2-tagger-v2"
-VIT_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-vit-tagger-v2"
+# MOAT_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-moat-tagger-v2"
+# SWIN_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-swinv2-tagger-v2"
+# CONV_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-convnext-tagger-v2"
+# CONV2_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-convnextv2-tagger-v2"
+# VIT_MODEL_DSV2_REPO = "SmilingWolf/wd-v1-4-vit-tagger-v2"
 
 # IdolSankaku series of models:
-EVA02_LARGE_MODEL_IS_DSV1_REPO = "deepghs/idolsankaku-eva02-large-tagger-v1"
-SWINV2_MODEL_IS_DSV1_REPO = "deepghs/idolsankaku-swinv2-tagger-v1"
+# EVA02_LARGE_MODEL_IS_DSV1_REPO = "deepghs/idolsankaku-eva02-large-tagger-v1"
+# SWINV2_MODEL_IS_DSV1_REPO = "deepghs/idolsankaku-swinv2-tagger-v1"
 
 # Files to download from the repos
 MODEL_FILENAME = "model.onnx"
@@ -56,8 +56,8 @@ class Predictor:
         self.last_loaded_repo = None
 
     def download_model(self, model_repo):
-        csv_path = huggingface_hub.hf_hub_download(model_repo, LABEL_FILENAME, use_auth_token=HF_TOKEN1)
-        model_path = huggingface_hub.hf_hub_download(model_repo, MODEL_FILENAME, use_auth_token=HF_TOKEN1)
+        csv_path = huggingface_hub.hf_hub_download(model_repo, LABEL_FILENAME, use_auth_token=HF_TOKEN)
+        model_path = huggingface_hub.hf_hub_download(model_repo, MODEL_FILENAME, use_auth_token=HF_TOKEN)
         return csv_path, model_path
 
     def load_model(self, model_repo):
@@ -123,20 +123,20 @@ def main():
     predictor = Predictor()
 
     model_repos = [
-        SWINV2_MODEL_DSV3_REPO,
-        CONV_MODEL_DSV3_REPO,
+        # SWINV2_MODEL_DSV3_REPO,
+        # CONV_MODEL_DSV3_REPO,
         VIT_MODEL_DSV3_REPO,
-        VIT_LARGE_MODEL_DSV3_REPO,
-        EVA02_LARGE_MODEL_DSV3_REPO,
+        # VIT_LARGE_MODEL_DSV3_REPO,
+        # EVA02_LARGE_MODEL_DSV3_REPO,
         # ---
-        MOAT_MODEL_DSV2_REPO,
-        SWIN_MODEL_DSV2_REPO,
-        CONV_MODEL_DSV2_REPO,
-        CONV2_MODEL_DSV2_REPO,
-        VIT_MODEL_DSV2_REPO,
+        # MOAT_MODEL_DSV2_REPO,
+        # SWIN_MODEL_DSV2_REPO,
+        # CONV_MODEL_DSV2_REPO,
+        # CONV2_MODEL_DSV2_REPO,
+        # VIT_MODEL_DSV2_REPO,
         # ---
-        SWINV2_MODEL_IS_DSV1_REPO,
-        EVA02_LARGE_MODEL_IS_DSV1_REPO,
+        # SWINV2_MODEL_IS_DSV1_REPO,
+        # EVA02_LARGE_MODEL_IS_DSV1_REPO,
     ]
 
     predefined_tags = ["loli",