Instructions to use Cournane/roberta-base-reduced-Upper_fabric with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Upper_fabric with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Upper_fabric")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Upper_fabric") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Upper_fabric") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e76dfc703d10916bceaad2debda9eecffe0f5037de51b4a1cb6abb6451d4c3f
- Size of remote file:
- 499 MB
- SHA256:
- e4b79ca122ccf34df26b994fe674519c49accd560fb7b15f4a94062a8613d5a5
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