add inference

app.py

@@ -178,7 +178,7 @@ def generate_image_with_steps(prompt, negative_prompt, seed, width, height, guid
     prompts =  [prompt]
     sampler = UniPCSampler(pipe,model_closure=model_closure, steps=num_inference_steps, guidance_scale=guidance_scale)
     c = prompts
-    uc = [negative_prompt] * len(c) if guidance_scale != 1.0 else None
+    uc = ['(worst quality:2), (low quality:2), (normal quality:2), bad anatomy, bad proportions, poorly drawn face, poorly drawn hands, missing fingers, extra limbs, blurry, pixelated, distorted, lowres, jpeg artifacts, watermark, signature, text, (deformed:1.5), (bad hands:1.3), overexposed, underexposed, censored, mutated, extra fingers, cloned face, bad eyes'] * len(c) if guidance_scale != 1.0 else None
     shape = [4, width // 8, height // 8]
                     # if opt.method == "dpm_solver_v3":
                             # batch_size, shape, conditioning, x_T, unconditional_conditioning
@@ -316,7 +316,7 @@ with gr.Blocks(css=css) as demo:
         fn=infer,
         inputs=[
             prompt,
-            '(worst quality:2), (low quality:2), (normal quality:2), bad anatomy, bad proportions, poorly drawn face, poorly drawn hands, missing fingers, extra limbs, blurry, pixelated, distorted, lowres, jpeg artifacts, watermark, signature, text, (deformed:1.5), (bad hands:1.3), overexposed, underexposed, censored, mutated, extra fingers, cloned face, bad eyes',
+            negative_prompt,
             seed,
             randomize_seed,
             resolution,