Update app.py

app.py

@@ -1,5 +1,7 @@
 import huggingface_hub
-huggingface_hub.login('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')
+import os
+hf_token = os.getenv('HF_TOKEN')
+huggingface_hub.login(hf_token)
 
 ###
 
@@ -26,6 +28,8 @@ processor = CLIPProcessor.from_pretrained('openai/clip-vit-large-patch14')
 
 import gradio as gr
 import numpy as np
+from torch.nn.functional import cosine_similarity
+
 
 def inference(prompt, negative_prompt, num_samples, height, width, num_inference_steps, guidance_scale, seed, top_k):
     g_cuda = torch.Generator(DEVICE)
@@ -33,7 +37,7 @@ def inference(prompt, negative_prompt, num_samples, height, width, num_inference
     with torch.autocast(DEVICE), torch.inference_mode():
         images = pipe(
             prompt, height=int(height), width=int(width),
-            negative_prompt=negative_prompt,
+            negative_prompt='ugly nerd with distorted fingers' + negative_prompt,
             num_images_per_prompt=int(num_samples),
             num_inference_steps=int(num_inference_steps), 
             guidance_scale=guidance_scale,
@@ -52,7 +56,7 @@ with gr.Blocks() as demo:
     with gr.Row():
         with gr.Column():
             prompt = gr.Textbox(label='Prompt', value='photo of <Dmitry> <thumbs-up>')
-            negative_prompt = gr.Textbox(label='Negative Prompt', value='ugly nerd with distorted fingers')
+            negative_prompt = gr.Textbox(label='Negative Prompt', value='')
             run = gr.Button(value='Generate')
             guidance_scale = gr.Number(label='Guidance Scale', value=7.5)
             with gr.Row():