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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4cc7c6ec32d2932ecece0dab13c3e24931e062e1717c5a77fc3f1dea516398a4
- Size of remote file:
- 3.58 kB
- SHA256:
- 408481cc4fc3d81450954ba14471ee245bf01e47f4625f894d9d7ab728956816
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