Update app.py

app.py

@@ -11,17 +11,17 @@ model_id = "CompVis/stable-diffusion-v1-4"
 device = "cuda"
 
 #If you are running this code locally, you need to either do a 'huggingface-cli login` or paste your User Access Token from here https://huggingface.co/settings/tokens into the use_auth_token field below. 
-pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=False, revision="fp16", torch_dtype=torch.float16)
+pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token="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", revision="fp16", torch_dtype=torch.float16)
 pipe = pipe.to(device)
 #When running locally, you won`t have access to this, so you can remove this part
-word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
-word_list = word_list_dataset["train"]['text']
+#word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
+#word_list = word_list_dataset["train"]['text']
 
 def infer(prompt, samples, steps, scale, seed):
     #When running locally you can also remove this filter
-    for filter in word_list:
-        if re.search(rf"\b{filter}\b", prompt):
-            raise gr.Error("Unsafe content found. Please try again with different prompts.")
+    #for filter in word_list:
+    #    if re.search(rf"\b{filter}\b", prompt):
+    #        raise gr.Error("Unsafe content found. Please try again with different prompts.")
         
     generator = torch.Generator(device=device).manual_seed(seed)