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app.py

@@ -19,15 +19,12 @@ from optimum.intel.openvino.modeling_diffusion import OVModelVaeDecoder, OVBaseM
 
 import os
 from tqdm import tqdm
-import gradio_user_history as gr_user_history
 
 from concurrent.futures import ThreadPoolExecutor
 import uuid
 
 DESCRIPTION = '''# Latent Consistency Model OpenVino CPU
-Based on [Latency Consistency Model](https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model) HF space 
-
-Distilled from [Dreamshaper v7](https://huggingface.co/Lykon/dreamshaper-7) fine-tune of [Stable Diffusion v1-5](https://huggingface.co/runwayml/stable-diffusion-v1-5) with only 4,000 training iterations (~32 A100 GPU Hours). [Project page](https://latent-consistency-models.github.io)
+Based on [Latency Consistency Model](https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model) HF space
 
 <p>Running on CPU 🥶.</p>
 '''
@@ -35,7 +32,7 @@ Distilled from [Dreamshaper v7](https://huggingface.co/Lykon/dreamshaper-7) fine
 MAX_SEED = np.iinfo(np.int32).max
 CACHE_EXAMPLES = os.getenv("CACHE_EXAMPLES") == "1"
 
-model_id = "deinferno/LCM_Dreamshaper_v7-openvino"
+model_id = "Kano001/Dreamshaper_v7-Openvino"
 batch_size = 1
 width = int(os.getenv("IMAGE_WIDTH", "512"))
 height = int(os.getenv("IMAGE_HEIGHT", "512"))
@@ -52,7 +49,7 @@ pipe = OVLatentConsistencyModelPipeline.from_pretrained(model_id, scheduler = sc
 
 # Inject TAESD
 
-taesd_dir = snapshot_download(repo_id="deinferno/taesd-openvino")
+taesd_dir = snapshot_download(repo_id="Kano001/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)
@@ -66,7 +63,6 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
 def save_image(img, profile: gr.OAuthProfile | None, metadata: dict):
     unique_name = str(uuid.uuid4()) + '.png'
     img.save(unique_name)
-    gr_user_history.save_image(label=metadata["prompt"], image=img, profile=profile, metadata=metadata)
     return unique_name
 
 def save_images(image_array, profile: gr.OAuthProfile | None, metadata: dict):
@@ -157,9 +153,6 @@ with gr.Blocks(css="style.css") as demo:
                 step=1,
                 value=4,
             )
-
-    with gr.Accordion("Past generations", open=False):
-        gr_user_history.render()
     
     gr.Examples(
         examples=examples,
@@ -189,4 +182,4 @@ with gr.Blocks(css="style.css") as demo:
 if __name__ == "__main__":
     demo.queue(api_open=False)
     # demo.queue(max_size=20).launch()
-    demo.launch()
+    demo.launch()

requirements.txt

@@ -9,5 +9,3 @@ optimum==1.13.2
 optimum-intel==1.11.0
 onnx==1.14.1
 transformers==4.31.0
-
-git+https://huggingface.co/spaces/Wauplin/gradio-user-history