Instructions to use priyabrat/Categorisation_article_latest_bert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use priyabrat/Categorisation_article_latest_bert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="priyabrat/Categorisation_article_latest_bert")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("priyabrat/Categorisation_article_latest_bert") model = AutoModelForSequenceClassification.from_pretrained("priyabrat/Categorisation_article_latest_bert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9df516f9a96da94ba2c819c65bbd28ad2646cb19c56d3b8465a6c9b02f640c0e
- Size of remote file:
- 438 MB
- SHA256:
- 5090d9e4f67c8d4cdfc2cee45b64d1de873cde0c19255a7bf7b9c62b24a5a04b
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