schnell

app.py

@@ -11,8 +11,8 @@ dtype = torch.bfloat16
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 taef1 = AutoencoderTiny.from_pretrained("madebyollin/taef1", torch_dtype=dtype).to(device)
-good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="vae", torch_dtype=dtype).to(device)
-pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=dtype, vae=taef1).to(device)
+good_vae = AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-schnell", subfolder="vae", torch_dtype=dtype).to(device)
+pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-schnell", torch_dtype=dtype, vae=taef1).to(device)
 torch.cuda.empty_cache()
 
 MAX_SEED = np.iinfo(np.int32).max