Instructions to use MesserMMP/news-classification-transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MesserMMP/news-classification-transformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MesserMMP/news-classification-transformer")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MesserMMP/news-classification-transformer") model = AutoModelForSequenceClassification.from_pretrained("MesserMMP/news-classification-transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2de2f0d177d8f0e7b53af366de9867e7f852ad5a2b3bfefaf963dc6047656680
- Size of remote file:
- 5.3 kB
- SHA256:
- 6f60253e4cf71c7c091ea43c62e44c8877fc278156055fc36432fc104a402de3
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