Instructions to use cesaredteam/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cesaredteam/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cesaredteam/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cesaredteam/results") model = AutoModelForSequenceClassification.from_pretrained("cesaredteam/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7c6b37a1f38f01d68f5e134763ac5083ab475af21d26ec1a57d6347941f68bff
- Size of remote file:
- 5.78 kB
- SHA256:
- 10886c809eac150441ee10140ba9f718112772a4f305f55a945b53ceefa3318a
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