Instructions to use sara-nabhani/ML-ns-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sara-nabhani/ML-ns-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sara-nabhani/ML-ns-roberta-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sara-nabhani/ML-ns-roberta-base") model = AutoModelForSequenceClassification.from_pretrained("sara-nabhani/ML-ns-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 995d471707a1268acca02540c57a13d2699f18706e3c1d05249288eeb66e8850
- Size of remote file:
- 499 MB
- SHA256:
- 35bd91110613fe7877c76b91297ad8201cf5703da51f3bdc0e676d1c1c854064
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