Instructions to use Jeevesh8/bert_ft_cola-80 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-80 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-80")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-80") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-80") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- adeac91773087ddd9b49c3f01d6b0868274c798e76c303d2061671c4bb655b96
- Size of remote file:
- 438 MB
- SHA256:
- 320a1e6f317f285a070f54aad34329a4b9ae7949eb1cc55df4e2643fcbc223f8
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