Instructions to use dtorber/roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dtorber/roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dtorber/roberta-base", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dtorber/roberta-base") model = AutoModelForSequenceClassification.from_pretrained("dtorber/roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aa6cdf0a67602a9559e43054fd60807da92bb4186da63bd960ba1f1232dfd938
- Size of remote file:
- 499 MB
- SHA256:
- e456870881a211422d0c243f7ae2800c1533961e1bd62c9027a252ab98e153b6
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