Update app.py

app.py

@@ -6,23 +6,13 @@ import random
 import time
 from diffusers import AutoPipelineForText2Image
 from diffusers import AutoPipelineForImage2Image
-from diffusers import FluxPipeline
+
 from diffusers.utils import load_image
 pipeline_text2image = AutoPipelineForText2Image.from_pretrained("stabilityai/sdxl-turbo").to("cuda")
 pipeline_image2image = AutoPipelineForImage2Image.from_pipe(pipeline_text2image).to("cuda")
-pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16).to("cuda")
 
 def text2img(prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe.",model="flux",guidance_scale=0.0, num_inference_steps=1):
-    if model=="flux":
-        image = pipe(
-            prompt,
-            guidance_scale=guidance_scale,
-            num_inference_steps=num_inference_steps,
-            max_sequence_length=256,
-            generator=torch.Generator("cpu").manual_seed(0)
-        ).images[0]
-    else:
-        image = pipeline_text2image(prompt=prompt, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
+    image = pipeline_text2image(prompt=prompt, guidance_scale=guidance_scale, num_inference_steps=num_inference_steps).images[0]
     return image
 
 def img2img(image,prompt="A cinematic shot of a baby racoon wearing an intricate italian priest robe.", guidance_scale=0.0, num_inference_steps=1,strength=0.5):