Update app.py

app.py

@@ -9,7 +9,13 @@ from transformers import CLIPTextModel, CLIPTokenizer,T5EncoderModel, T5Tokenize
 dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
-pipe = FluxPipeline.from_pretrained("sayakpaul/FLUX.1-merged", torch_dtype=torch.bfloat16).to(device)
+model_id = "black-forest-labs/FLUX.1-dev"
+adapter_id = "alimama-creative/FLUX.1-Turbo-Alpha"
+
+pipe = FluxPipeline.from_pretrained(model_id, torch_dtype=dtype).to(device)
+
+pipe.load_lora_weights(adapter_id)
+pipe.fuse_lora()
 
 MAX_SEED = np.iinfo(np.int32).max
 MAX_IMAGE_SIZE = 2048
@@ -26,7 +32,8 @@ def infer(prompt, seed=42, randomize_seed=False, width=1024, height=1024, guidan
         height = height,
         num_inference_steps = num_inference_steps, 
         generator = generator,
-        guidance_scale=guidance_scale
+        guidance_scale=guidance_scale,
+        max_sequence_length=512
     ).images[0] 
     return image, seed