Instructions to use Cournane/roberta-base-reduced-Neckline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Neckline with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Neckline")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Neckline") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Neckline") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 70ccf982ddf8dada40d9443818b3d13395b50f692276e4efa104021f97181707
- Size of remote file:
- 499 MB
- SHA256:
- 198764acb0b778c9fecadc3a2ac347ec42ead0192da91b7f32c35deb5d09eba5
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