Instructions to use Jeevesh8/bert_ft_cola-33 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-33 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-33")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-33") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-33") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f4182a4a57120a89def7facb1e2aaef3c9f90ca1101cffa6e779940f211d25e7
- Size of remote file:
- 438 MB
- SHA256:
- 7d2a01ad2dfa86107fe35d76bbc0d3d14dddb06e688dd343185106b146a295fc
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