Instructions to use pmthangk09/bert-base-uncased-glue-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pmthangk09/bert-base-uncased-glue-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pmthangk09/bert-base-uncased-glue-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pmthangk09/bert-base-uncased-glue-cola") model = AutoModelForSequenceClassification.from_pretrained("pmthangk09/bert-base-uncased-glue-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 453e7eee188349fd7f67748b7cabb51f168144c219d6a541ae1cc619920532e1
- Size of remote file:
- 438 MB
- SHA256:
- b59dfdf61e81fd8c89bc4ff79fc76737df94326f8a6b61b25aceb1cbb0f1423c
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