Update app.py

app.py

@@ -12,32 +12,18 @@ import spaces
 from huggingface_hub import hf_hub_download
 from optimum.quanto import freeze, qfloat8, quantize
 
-# Load fp8
-#transformer = FluxTransformer2DModel.from_single_file("https://huggingface.co/Kijai/flux-fp8/blob/main/flux1-dev-fp8.safetensors", torch_dtype=torch.bfloat16)
-#quantize(transformer, weights=qfloat8)
-#freeze(transformer)
-
-# Load models
-#controlnet = FluxControlNetModel.from_pretrained("alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha", torch_dtype=torch.bfloat16)
-#quantize(controlnet, weights=qfloat8)
-#freeze(controlnet)
+
 controlnet = FluxControlNetModel.from_pretrained("alimama-creative/FLUX.1-dev-Controlnet-Inpainting-Alpha", torch_dtype=torch.bfloat16)
 transformer = FluxTransformer2DModel.from_pretrained(
     "black-forest-labs/FLUX.1-dev", subfolder='transformer', torch_dtype=torch.bfloat16
 )
 
-text_encoder_2 = T5EncoderModel.from_pretrained("black-forest-labs/FLUX.1-dev", subfolder="text_encoder_2", torch_dtype=torch.bfloat16)
-quantize(text_encoder_2, weights=qfloat8)
-freeze(text_encoder_2)
-
 pipe = FluxControlNetInpaintingPipeline.from_pretrained(
     "black-forest-labs/FLUX.1-dev",
-    text_encoder_2=None,
     transformer=transformer,
     controlnet=controlnet,
     torch_dtype=torch.bfloat16
 )
-pipe.text_encoder_2 = text_encoder_2
 
 repo_name = "ByteDance/Hyper-SD"
 ckpt_name = "Hyper-FLUX.1-dev-8steps-lora.safetensors"