Instructions to use Songnguyen263/MultiLabel-Emotion-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Songnguyen263/MultiLabel-Emotion-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Songnguyen263/MultiLabel-Emotion-Classification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Songnguyen263/MultiLabel-Emotion-Classification") model = AutoModelForSequenceClassification.from_pretrained("Songnguyen263/MultiLabel-Emotion-Classification") - Notebooks
- Google Colab
- Kaggle
Initial tokenizer upload
Browse files- tokenizer_config.json +1 -1
tokenizer_config.json
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@@ -51,6 +51,6 @@
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "
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"unk_token": "[UNK]"
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}
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"sep_token": "[SEP]",
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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}
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