Update app.py

app.py

@@ -38,8 +38,8 @@ taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.b
 good_vae = AutoencoderKL.from_pretrained("ostris/Flex.1-alpha", subfolder="vae", torch_dtype=torch.bfloat16).to(device)
 
 dtype = torch.bfloat16
-base_model = "AlekseyCalvin/HSTcolor_FlexSoonr"
-pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype).to("cuda")
+base_model = ""AlekseyCalvin/FlexAlpha_Soonr"
+pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=dtype, use_safetensors=True).to("cuda")
 #pipe.vae = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=torch.float16).to("cuda")
 torch.cuda.empty_cache()
 
@@ -55,6 +55,8 @@ pipe.text_encoder.dtype = torch.bfloat16
 
 pipe.vae = AutoencoderKL.from_pretrained("ostris/Flex.1-alpha", subfolder="vae", torch_dtype=dtype).to(device)
 
+pipe.flux_pipe_call_that_returns_an_iterable_of_images = flux_pipe_call_that_returns_an_iterable_of_images.__get__(pipe)
+
 # Load LoRAs from JSON file
 with open('loras.json', 'r') as f:
     loras = json.load(f)