Update app.py

app.py

@@ -5,28 +5,14 @@ import os
 # model = gr.load("models/prithivMLmods/SD3.5-Turbo-Realism-2.0-LoRA") # <-- This model is also working
 model = gr.load("models/Purz/face-projection")
 
-
-default_negative_prompt = (
-    "Extra limbs, Extra fingers or toes, Disfigured face, Distorted hands, Mutated body parts, "
-    "Missing limbs, Asymmetrical features, Blurry face, Poor anatomy, Incorrect proportions, Crooked eyes, "
-    "Deformed hands or fingers, Double face, Unrealistic skin texture, Overly smooth skin, Poor lighting, "
-    "Cartoonish appearance, Plastic look, Grainy, Unnatural expressions, Crossed eyes, Mutated clothing, "
-    "Artifacts, Uncanny valley, Doll-like features, Bad symmetry, Uneven skin tones, Extra teeth, "
-    "Unrealistic hair texture, Dark shadows on face, Overexposed face, Cluttered background, Text, watermark, "
-    "or signature, Over-processed, Low quality, Blurry, Low resolution, Pixelated, Oversaturated, Too dark, Overexposed, Poor lighting, "
-    "Unclear, Text or watermark, Distorted faces, Extra limbs or fingers, Disfigured, Grainy, Overly stylized, Cartoonish, "
-    "Unrealistic anatomy, Bad proportions, Unrealistic colors, Artificial look, Background noise, Unwanted objects, Repetitive patterns, Artifacting, Abstract shapes, Out of focus"
-)
-
-def generate_image(text, seed, width, height, guidance_scale, num_inference_steps, negative_prompt=default_negative_prompt):
+def generate_image(text, seed, width, height, guidance_scale, num_inference_steps):
     if seed is not None:
         random.seed(seed)
 
     if text in [example[0] for example in examples]:
         print(f"Using example: {text}")
 
-
-    result_image = model(text, negative_prompt=negative_prompt)
+    result_image = model(text)
     
     print(f"Width: {width}, Height: {height}, Guidance Scale: {guidance_scale}, Inference Steps: {num_inference_steps}")