Instructions to use Jeevesh8/bert_ft_cola-83 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-83 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-83")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-83") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-83") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 633b32b0d10f2dfce44c711199cc5bf5da7c41cfea0ab57d401807137292abfd
- Size of remote file:
- 438 MB
- SHA256:
- b86d0126daf36b977c80b2413133631d9a0c244fb7041ca552a62d175be47c8f
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