Instructions to use alfredodeza/trail_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alfredodeza/trail_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="alfredodeza/trail_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("alfredodeza/trail_classifier") model = AutoModelForSequenceClassification.from_pretrained("alfredodeza/trail_classifier") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2807816ef176d46d199a708e50a90499ea2384e2f46e1426729f6ec39a51fe15
- Size of remote file:
- 5.84 kB
- SHA256:
- ec3ec7a981b47344a91f3e8d21e7ebc9148d636b8926f6f0465995aa6b5a0cfd
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