Instructions to use Harsh-7300/bert_trained with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harsh-7300/bert_trained with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Harsh-7300/bert_trained")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Harsh-7300/bert_trained") model = AutoModelForSequenceClassification.from_pretrained("Harsh-7300/bert_trained") - Notebooks
- Google Colab
- Kaggle
Update tokenizer.json
Browse files- tokenizer.json +7 -0
tokenizer.json
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{
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"model_type": "bert",
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"do_lower_case": true,
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"strip_accents": false,
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"pad_token_id": 0,
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"wordpieces_prefix": "##"
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}
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