Instructions to use Jeevesh8/6ep_bert_ft_cola-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/6ep_bert_ft_cola-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/6ep_bert_ft_cola-13")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/6ep_bert_ft_cola-13") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/6ep_bert_ft_cola-13") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2639c6db28b4546ace4d83f44a6e5926732dd7431b18da87f18b6500eeffefc
- Size of remote file:
- 438 MB
- SHA256:
- 308f5df22cb1ede5441386a0db8548a9b667cb8b0459b90e1a308e0f954ae62d
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