Instructions to use Cournane/roberta-base-reduced-Lower_fabric with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Lower_fabric with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Lower_fabric")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Lower_fabric") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Lower_fabric") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 792b17ae89f9da39285052e6ff3b674ebf0bc5fc8f882df1e1e5ee997593d1a9
- Size of remote file:
- 499 MB
- SHA256:
- d00973f1d657a75f2ba9a42ce49324e005a0efefe611771f621d1cfa7e0f796d
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