Instructions to use ModelTC/roberta-base-qnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/roberta-base-qnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/roberta-base-qnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/roberta-base-qnli") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/roberta-base-qnli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4b84a7940dcb996e1295a6148ffcb4c2f06089e86dab4d712eaafdedda1d77a8
- Size of remote file:
- 499 MB
- SHA256:
- a2690e3b2c07a985122d73821a19ba7d088f4fb8d3871d256b167251f1b2e1ef
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