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Update README.md

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  license: openrail
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  license: openrail
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+ import torch
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+ from transformers import AutoTokenizer, MobileBertForSequenceClassification
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+
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+ # Load the saved model
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+ model_name = 'harshith20/Emotion_predictor'
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = MobileBertForSequenceClassification.from_pretrained(model_name)
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+
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+ # Tokenize input text
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+ input_text = "I am feeling happy today"
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+ encoded_text = tokenizer.encode_plus(
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+ input_text,
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+ max_length=128,
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+ padding='max_length',
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+ truncation=True,
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+ return_attention_mask=True,
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+ return_tensors='pt'
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+ )
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+
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+ # Predict emotion
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+ with torch.no_grad():
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+ logits = model(**encoded_text)[0]
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+ predicted_emotion = torch.argmax(logits).item()
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+ emotion_labels = ['anger', 'fear', 'joy', 'love', 'sadness', 'surprise']
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+ predicted_emotion_label = emotion_labels[predicted_emotion]
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+
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+ print(f"Input text: {input_text}")
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+ print(f"Predicted emotion: {predicted_emotion_label}")