remove Flux2-TAE

app.py

@@ -1,7 +1,7 @@
 import spaces
 import gradio as gr
 import torch
-from diffusers import AutoencoderKL, AutoencoderDC, AutoModel
+from diffusers import AutoencoderKL, AutoencoderDC
 from diffusers.utils.remote_utils import remote_decode
 import torchvision.transforms.v2 as transforms
 from torchvision.io import read_image
@@ -66,7 +66,6 @@ class VAETester:
 			# "dc-ae-f32c32-sana-1.0": AutoencoderDC.from_pretrained("mit-han-lab/dc-ae-f32c32-sana-1.0-diffusers").to(self.device),
             "FLUX.1-Kontext": AutoencoderKL.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", subfolder="vae").to(self.device),
             "FLUX.2": AutoencoderKL.from_pretrained("black-forest-labs/FLUX.2-dev", subfolder="vae").to(self.device),
-            "FLUX.2-TinyAutoEncoder": AutoModel.from_pretrained("fal/FLUX.2-Tiny-AutoEncoder", trust_remote_code=True).to(self.device),
         }
         # Define the desired order of models
         order = [
@@ -85,7 +84,6 @@ class VAETester:
 			# "dc-ae-f32c32-sana-1.0",
             "FLUX.1-Kontext",
             "FLUX.2",
-            "FLUX.2-TinyAutoEncoder",
         ]
 
         # Construct the vae_models dictionary in the specified order