Instructions to use nmcahill/mtbi-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nmcahill/mtbi-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nmcahill/mtbi-classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nmcahill/mtbi-classifier") model = AutoModelForSequenceClassification.from_pretrained("nmcahill/mtbi-classifier") - Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json (#2)
Browse files- Update tokenizer_config.json (10396290f6d85d6064b0df9ea79b0d068847d070)
- tokenizer_config.json +6 -6
tokenizer_config.json
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{
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{"distilbert-base-uncased": {"do_lower_case": true},
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"distilbert-base-uncased-distilled-squad": {"do_lower_case": true},
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"distilbert-base-cased": {"do_lower_case": false},
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"distilbert-base-cased-distilled-squad": {"do_lower_case": false},
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"distilbert-base-german-cased": {"do_lower_case": false},
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"distilbert-base-multilingual-cased": {"do_lower_case": false}}
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