Instructions to use icfrowne/classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use icfrowne/classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="icfrowne/classification")# Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("icfrowne/classification") model = AutoModelForSequenceClassification.from_pretrained("icfrowne/classification") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78ba8851b20a00a52f7a115c4496312434f13cee359a1d2373154831ccccdd9d
- Size of remote file:
- 802 MB
- SHA256:
- 27652095ebb7f4cd5c8badb47cb711d39639bbbe2e57b32d3fb98e83e5b35662
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