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Update README.md

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@@ -39,8 +39,9 @@ You can use this model directly with a pipeline for text classification, or you
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  First, install the transformers library if you haven't already:
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  ```bash
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  pip install transformers
 
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-
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  from transformers import AutoModelForSequenceClassification, AutoTokenizer
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  import torch
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@@ -64,6 +65,8 @@ predicted_class_index = probabilities.argmax().item()
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  labels = ["az", "ar", "bg", "de", "el", "en", "es", "fr", "hi", "it", "ja", "nl", "pl", "pt", "ru", "sw", "th", "tr", "ur", "vi", "zh"]
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  predicted_label = labels[predicted_class_index]
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  print(f"Predicted Language: {predicted_label}")
 
 
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  Training Performance
 
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  First, install the transformers library if you haven't already:
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  ```bash
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  pip install transformers
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+ ```
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+ ```
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  from transformers import AutoModelForSequenceClassification, AutoTokenizer
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  import torch
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  labels = ["az", "ar", "bg", "de", "el", "en", "es", "fr", "hi", "it", "ja", "nl", "pl", "pt", "ru", "sw", "th", "tr", "ur", "vi", "zh"]
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  predicted_label = labels[predicted_class_index]
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  print(f"Predicted Language: {predicted_label}")
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+ ```
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+
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  Training Performance