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--- |
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language: en |
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tags: |
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- text-classification |
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- pytorch |
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license: apache-2.0 |
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datasets: |
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- emotion |
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--- |
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```python |
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from transformers import pipeline |
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model_id = "suvrobaner/distilbert-base-uncased-finetuned-emotion-en-tweets" |
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classifier = pipeline("text-classification", model = model_id) |
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custom_tweet = "I saw a movie today and it was really good." |
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preds = classifier(custom_tweet, return_all_scores=True) |
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labels = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise'] |
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preds_df = pd.DataFrame(preds[0]) |
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import matplotlib.pyplot as plt |
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plt.bar(labels, 100 * preds_df["score"], color='C0') |
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plt.title(f'"{custom_tweet}"') |
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plt.ylabel("Class probability (%)") |
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plt.show() |
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``` |
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