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|
| | from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
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| | |
| | model_name = "HooshvareLab/bert-fa-base-uncased-sentiment-snappfood" |
| |
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| | |
| | tokenizer = AutoTokenizer.from_pretrained(model_name) |
| | model = AutoModelForSequenceClassification.from_pretrained(model_name) |
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|
| | |
| | sentiment_pipeline = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer) |
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|
| | |
| | texts = [ |
| | "من این فیلم را خیلی دوست دارم", |
| | "این غذا افتضاح بود", |
| | "امروز یک روز معمولی است" |
| | ] |
| |
|
| | for t in texts: |
| | result = sentiment_pipeline(t) |
| | print(f"متن: {t}") |
| | print(f"نتیجه: {result}\n") |