Instructions to use Cheng98/bert-base-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cheng98/bert-base-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cheng98/bert-base-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cheng98/bert-base-cola") model = AutoModelForSequenceClassification.from_pretrained("Cheng98/bert-base-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b6673f55e39077e70536be056053f8e49e2d14288af250cc29aca5874a77e9c8
- Size of remote file:
- 438 MB
- SHA256:
- 4e8e24029a5745a1db305a69476cb2c75f3c028ad0f01e9169121d8010e1202e
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