ml-debi commited on
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d5e2227
1 Parent(s): 8d8e13c

Update my_app.py

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  1. my_app.py +5 -3
my_app.py CHANGED
@@ -6,16 +6,18 @@ from tensorflow.keras import mixed_precision
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  # Load your trained models
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  #model1 = from_pretrained_keras("ml-debi/EfficientNetB0-Food101")
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  #model2 = from_pretrained_keras("ml-debi/EfficientNetB0-Food101")
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- model1 = from_pretrained_keras("ml-debi/test_model")
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  with open('classes.txt', 'r') as f:
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  classes = [line.strip() for line in f]
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  # Add information about the models
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  model1_info = """
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- ### Model 1 Information
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- This model is based on the EfficientNetB0 architecture and was trained on the Food101 dataset.
 
 
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  """
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  #model2_info = """
 
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  # Load your trained models
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  #model1 = from_pretrained_keras("ml-debi/EfficientNetB0-Food101")
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  #model2 = from_pretrained_keras("ml-debi/EfficientNetB0-Food101")
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+ model1 = from_pretrained_keras("ml-debi/EfficientNetV2S-Food101")
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  with open('classes.txt', 'r') as f:
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  classes = [line.strip() for line in f]
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  # Add information about the models
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  model1_info = """
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+ ### Model Information
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+ Welcome to my Hugging Face space, where gastronomy meets technology! This space is dedicated to an image classifier that has been trained on the Food101 dataset.
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+ At the core of this classifier lies the EfficientNetV2S base model, which has been fine-tuned to enhance its ability to identify a broad spectrum of food items with great accuracy.
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+ While it may not be perfect, it’s a nice tool for culinary exploration. Enjoy your journey through the world of food! 🍽️
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  """
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  #model2_info = """