Instructions to use Cournane/roberta-base-reduced-Ring with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-reduced-Ring with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-reduced-Ring")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-reduced-Ring") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-reduced-Ring") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 861dc28e9adcfecfd2196c9a45d0aaba1a47e371eaaedd93d3419976d2153515
- Size of remote file:
- 499 MB
- SHA256:
- 8d54f8f5570a64a641c6078cc0aa69957235a6e1e777cddc455db9ed2fbb4231
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