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+ A model fine-tuned for sentiment analysis based on [vinai/phobert-base](https://huggingface.co/vinai/phobert-base).
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+
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+ Labels:
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+ - NEG: Negative
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+ - POS: Positive
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+ - NEU: Neutral
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+
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+ Dataset: Comments on Shoppe (https://shopee.vn/)
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+ ## Usage
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+ from transformers import AutoTokenizer, AutoModelForSequenceClassification
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+ import torch
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+
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+ tokenizer = AutoTokenizer.from_pretrained("lamsytan/sentiment-analysis-base-phobert")
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+ model = AutoModelForSequenceClassification.from_pretrained("lamsytan/sentiment-analysis-base-phobert")
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+
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+ sentence = "Áo đẹp lắm nhá lần sau sẽ ghé tiếp ạ"
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+
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+ inputs = tokenizer(sentence, return_tensors="pt", padding=True, truncation=True)
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+
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+ with torch.no_grad():
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+ outputs = model(**inputs)
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+ logits = outputs.logits
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+ probabilities = torch.softmax(logits, dim=-1)
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+
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+ print(probabilities.tolist())
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+ # Output:
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+ # [[0.010827462188899517, 0.9538241624832153, 0.035348404198884964]]
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+ # ^ ^ ^
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+ # NEG POS NEU
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+