Instructions to use lewtun/bert-base-uncased-finetuned-boolq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lewtun/bert-base-uncased-finetuned-boolq with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lewtun/bert-base-uncased-finetuned-boolq")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lewtun/bert-base-uncased-finetuned-boolq") model = AutoModelForSequenceClassification.from_pretrained("lewtun/bert-base-uncased-finetuned-boolq", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0694e373dadc07129e1a5253d3940f470d0860f861f2f9f6f01311f79dd6c14
- Size of remote file:
- 438 MB
- SHA256:
- b6704a9272f407397ba2e1387c3c27dc49f8a72b25281c8c99ed336272edf442
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