Update app.py

app.py

@@ -3,9 +3,7 @@ import os
 import torch
 from torch import autocast
 from diffusers import StableDiffusionPipeline
-from datasets import load_dataset
 from PIL import Image
-import re
 from styles import css, header_html, footer_html
 from examples import examples
 from transformers import pipeline
@@ -20,10 +18,6 @@ device = "cuda" if torch.cuda.is_available() else "cpu"
 pipe = StableDiffusionPipeline.from_pretrained(
     model_id, use_auth_token=True, 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=os.environ.get('auth_token')
-word_list = word_list_dataset["train"]['text']
 
 
 def transcribe(audio):
@@ -32,13 +26,8 @@ def transcribe(audio):
 
 
 def infer(audio, samples, steps, scale, seed):
-    prompt = transcribe(audio)
-    # 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.")
 
+    prompt = transcribe(audio)
     generator = torch.Generator(device=device).manual_seed(seed)
 
     # If you are running locally with CPU, you can remove the `with autocast("cuda")`
@@ -131,4 +120,4 @@ with block:
         )
         gr.HTML(footer_html)
 
-block.queue(max_size=25).launch()
+block.queue(max_size=25).launch()