Instructions to use ModelTC/bert-base-uncased-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bert-base-uncased-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ModelTC/bert-base-uncased-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ModelTC/bert-base-uncased-cola") model = AutoModelForSequenceClassification.from_pretrained("ModelTC/bert-base-uncased-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1139d116504ba4bd1aaa786ed0d97fd7f647d080c4002be40bbe4716b3533eb8
- Size of remote file:
- 2.93 kB
- SHA256:
- d7c87eda243a161b5e182fefa4963ac8e04e3c64401935f3aaccfd8248a8441a
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