Update app.py

app.py

@@ -9,7 +9,6 @@ import gradio as gr
 import numpy as np
 import PIL.Image
 
-from huggingface_hub import snapshot_download
 from diffusers import DiffusionPipeline
 
 from optimum.intel.openvino.modeling_diffusion import OVModelVaeDecoder, OVBaseModel, OVStableDiffusionPipeline
@@ -28,6 +27,8 @@ Converted from [SoteMix](https://huggingface.co/Disty0/SoteMix) to [LCM_SoteMix]
 
 This model is for Anime art style.
 
+Faster but lower quality version with TAESD VAE: [LCM_SoteMix_OpenVINO_CPU_Space_TAESD](https://huggingface.co/spaces/Disty0/LCM_SoteMix_OpenVINO_CPU_Space_TAESD)
+
 [LCM Project page](https://latent-consistency-models.github.io)
 
 <p>Running on CPU with OpenVINO Acceleration</p>
@@ -43,19 +44,7 @@ height = int(os.getenv("IMAGE_HEIGHT", "512"))
 num_images = int(os.getenv("NUM_IMAGES", "1"))
 guidance_scale = float(os.getenv("GUIDANCE_SCALE", "1.0"))
 
-class CustomOVModelVaeDecoder(OVModelVaeDecoder):
-    def __init__(
-        self, model: openvino.runtime.Model, parent_model: OVBaseModel, ov_config: Optional[Dict[str, str]] = None, model_dir: str = None,
-    ):
-        super(OVModelVaeDecoder, self).__init__(model, parent_model, ov_config, "vae_decoder", model_dir)
-
 pipe = OVStableDiffusionPipeline.from_pretrained(model_id, compile = False, ov_config = {"CACHE_DIR":""})
-
-# Inject TAESD
-
-taesd_dir = snapshot_download(repo_id="deinferno/taesd-openvino")
-pipe.vae_decoder = CustomOVModelVaeDecoder(model = OVBaseModel.load_model(f"{taesd_dir}/vae_decoder/openvino_model.xml"), parent_model = pipe, model_dir = taesd_dir)
-
 pipe.reshape(batch_size=batch_size, height=height, width=width, num_images_per_prompt=num_images)
 pipe.compile()