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:
- 4627471140735d4eb986456e325783b2845d12fce4029b860d10a3f71c4b5559
- Size of remote file:
- 3.06 kB
- SHA256:
- 5d7e533e6f8c4ac84cdae12c2f7145c2b1bc77abace1df22bc26571bc3b6082a
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