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Update app.py
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app.py
CHANGED
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@@ -11,14 +11,14 @@ model = AutoModel.from_pretrained(model_ckpt)
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hidden_dim = model.config.hidden_size
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dataset = load_dataset("BounharAbdelaziz/Face-Aging-Dataset")
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MAX_K =
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# Find Your Twins
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Upload your face and find the most similar faces from [Face Aging Dataset](https://huggingface.co/datasets/BounharAbdelaziz/Face-Aging-Dataset) using Google's [VIT](https://huggingface.co/google/vit-base-patch16-224-in21k) model. For best results please use 1x1 ratio face images, take a look at examples. The Vector similarity search is powered by [Upstash Vector](https://upstash.com) 🚀. You can check our blog [post](https://huggingface.co/blog/omerXfaruq/serverless-image-similarity-with-upstash-vector) to learn more.
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"""
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)
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hidden_dim = model.config.hidden_size
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dataset = load_dataset("BounharAbdelaziz/Face-Aging-Dataset")
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MAX_K = 50
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# Find Your Twins
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Upload your face and find the most similar faces from [Face Aging Dataset](https://huggingface.co/datasets/BounharAbdelaziz/Face-Aging-Dataset) using Google's [VIT](https://huggingface.co/google/vit-base-patch16-224-in21k) model. For best results please use 1x1 ratio face images, take a look at examples. Also increasing count in the advanced section results with more accurate searches. The Vector similarity search is powered by [Upstash Vector](https://upstash.com) 🚀. You can check our blog [post](https://huggingface.co/blog/omerXfaruq/serverless-image-similarity-with-upstash-vector) to learn more.
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"""
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)
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