Instructions to use priyabrat/bert_categorisation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use priyabrat/bert_categorisation with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="priyabrat/bert_categorisation")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("priyabrat/bert_categorisation") model = AutoModelForSequenceClassification.from_pretrained("priyabrat/bert_categorisation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e455091cd360735b826b3516eaebb26ec0192cbb8c967c231af208a79618392
- Size of remote file:
- 438 MB
- SHA256:
- d91cdff5fc9a837c2735cf27cedf1e1cef7685bf3f880a25b5c77ca946d1acda
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