Instructions to use Waliguren/hackaton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Waliguren/hackaton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Waliguren/hackaton")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Waliguren/hackaton") model = AutoModelForSequenceClassification.from_pretrained("Waliguren/hackaton") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 81a479c30351e71252f6bfe6e85782f0f366081888f38acc2d872f0dbdfd6827
- Size of remote file:
- 439 MB
- SHA256:
- ad922e59b52322a226334b1816867a80707abacf72ff8e3e2d7c64a03dbb5886
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