Instructions to use ntatiit/bert-banking77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ntatiit/bert-banking77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ntatiit/bert-banking77")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ntatiit/bert-banking77") model = AutoModelForSequenceClassification.from_pretrained("ntatiit/bert-banking77") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files
README.md
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library_name: transformers
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license: cc
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datasets:
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- mteb/banking77
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base_model:
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- google-bert/bert-base-uncased
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base_model:
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library_name: transformers
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license: cc
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# Model Card for Model ID
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