Update app.py

app.py

@@ -53,9 +53,11 @@ torch_dtype = torch.bfloat16
 
 checkpoint = "microsoft/Phi-3.5-mini-instruct"
 #vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
-vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", torch_dtype=torch.bfloat16).to(torch.device("cuda:0"))
+#vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16", torch_dtype=torch.bfloat16).to(torch.device("cuda:0"))
+vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16")
 
-pipe = StableDiffusion3Pipeline.from_pretrained("ford442/stable-diffusion-3.5-medium-bf16", torch_dtype=torch.bfloat16).to(torch.device("cuda:0"))
+#pipe = StableDiffusion3Pipeline.from_pretrained("ford442/stable-diffusion-3.5-medium-bf16", torch_dtype=torch.bfloat16).to(torch.device("cuda:0"))
+pipe = StableDiffusion3Pipeline.from_pretrained("ford442/stable-diffusion-3.5-medium-bf16").to(torch.device("cuda:0"))
 #pipe = StableDiffusion3Pipeline.from_pretrained("ford442/RealVis_Medium_1.0b_bf16", torch_dtype=torch.bfloat16)
 #pipe = StableDiffusion3Pipeline.from_pretrained("stabilityai/stable-diffusion-3.5-medium", token=hftoken, torch_dtype=torch.float32, device_map='balanced')
 
@@ -144,7 +146,7 @@ def infer(
     outputs = model.generate(
         input_ids=input_ids,
         attention_mask=attention_mask,
-        max_new_tokens=65,
+        max_new_tokens=240,
         temperature=0.2,
         top_p=0.9,
         do_sample=True,
@@ -186,13 +188,16 @@ def infer(
         with torch.no_grad():
           sd_image = pipe(
             prompt=enhanced_prompt,  # This conversion is fine
+            prompt2=prompt,
+            prompt3=prompt,
             negative_prompt=negative_prompt,
             guidance_scale=guidance_scale,
             num_inference_steps=num_inference_steps,
             width=width,
             height=height,
-            latents=None,
-            generator=generator
+         #   latents=None,
+            generator=generator,
+            target_size=(width,height)
           ).images[0]
         print('-- got image --')
     image_path = f"sd35m_{seed}.png"