Instructions to use msterbentz/roberta-base-boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use msterbentz/roberta-base-boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="msterbentz/roberta-base-boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("msterbentz/roberta-base-boolq") model = AutoModelForSequenceClassification.from_pretrained("msterbentz/roberta-base-boolq") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f65bb1b3e41b9a62548f783e9adede2fea5da1be74266f64c0f7b6fd84ca51c7
- Size of remote file:
- 499 MB
- SHA256:
- 4ce0355b26eaa6aef1949d15eec511e73e155b70c32acad22676a8bad3419659
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