Instructions to use MikhailRepkin/news_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MikhailRepkin/news_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MikhailRepkin/news_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MikhailRepkin/news_classifier") model = AutoModelForSequenceClassification.from_pretrained("MikhailRepkin/news_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 95b9795a407c84af35c2e92e5ff8b8b69a40add85d0dee3717d0a406cae07b6f
- Size of remote file:
- 711 MB
- SHA256:
- 5f563a9fc78377574bd9d1809a823eaeab2800934bcbadfe74cc55735fe09218
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