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Update README.md

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@@ -15,7 +15,8 @@ Vehicle inspection automation
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  Fleet management optimization
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  🚀 Enhance your car damage prediction tasks with the llm VIT BEIT model. Experience unprecedented accuracy and reliability for a wide range of applications. Get started with Hugging Face integration today!
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  # First Approach
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- import numpy as np
 
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  from PIL import Image
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  from transformers import AutoImageProcessor, AutoModelForImageClassification
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@@ -33,8 +34,10 @@ label_map = model.config.id2label
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  predicted_class_name = label_map[predicted_class_id]
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  print(f"Predicted class: {predicted_class_name} (probability: {predicted_proba:.4f})")
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-
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  # 2nd Aprroach
 
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  from transformers import pipeline
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- pipe = pipeline("image-classification", model="beingamit99/car_damage_detection")
 
 
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  Fleet management optimization
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  🚀 Enhance your car damage prediction tasks with the llm VIT BEIT model. Experience unprecedented accuracy and reliability for a wide range of applications. Get started with Hugging Face integration today!
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  # First Approach
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+ <CODE>
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+ import numpy as np
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  from PIL import Image
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  from transformers import AutoImageProcessor, AutoModelForImageClassification
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  predicted_class_name = label_map[predicted_class_id]
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  print(f"Predicted class: {predicted_class_name} (probability: {predicted_proba:.4f})")
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+ </CODE>
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  # 2nd Aprroach
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+ <CODE>
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  from transformers import pipeline
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+ pipe = pipeline("image-classification", model="beingamit99/car_damage_detection")
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+ </CODE>