Instructions to use Jeevesh8/bert_ft_cola-12 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-12 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-12")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-12") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-12") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bf5f36a6f350296a1f26632e259a9233fe2fafbdfcaa76ac15d9f168aeb37839
- Size of remote file:
- 438 MB
- SHA256:
- 01c23f516b60768aa940d34cdb4df69c633ea1e1a473e63827f3eb143b2dec3f
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