Instructions to use Jeevesh8/bert_ft_cola-59 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-59 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-59")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-59") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-59") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4ad01949c3dc9ef1ea8a67f6c75fce967bab85923255478c7e760f1790f9ce7
- Size of remote file:
- 438 MB
- SHA256:
- ebdd95f4d0ae4d9955e84d02fd5c80dc4735bba2c95a27dffad7a0b8015b22f3
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