Instructions to use Jeevesh8/bert_ft_cola-39 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-39 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-39")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-39") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-39") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 528d9480eeca2e7fb0aed1e06622cff8d3caa7ba3130051f24bf91a5d9abb789
- Size of remote file:
- 438 MB
- SHA256:
- b56b484e4595908b6f1b47204d6cd896cc6cc18787e81dc5ed5bcaeeb4a42416
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