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
Create tokenizer_config.json (#1)
Browse files- Create tokenizer_config.json (3e7ed8159371aaef95a5c8eaee3958614853be45)
- tokenizer_config.json +6 -0
tokenizer_config.json
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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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