Instructions to use auspect/trail_classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use auspect/trail_classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="auspect/trail_classifier")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("auspect/trail_classifier") model = AutoModelForSequenceClassification.from_pretrained("auspect/trail_classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 867556e8e91b0b0a78c48b9e429a5f271cff8c9e7657dcb7d7ef28fd34939c7f
- Size of remote file:
- 438 MB
- SHA256:
- b12941281e56a4cd454eac196536058f50319a6e0e1541646edbd9edf9076493
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