Instructions to use Jeevesh8/bert_ft_cola-75 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-75 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-75")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-75") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-75") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c1f989b43bde5c13b409314c15b04b9931c5c407b91fada964298e848e99ba64
- Size of remote file:
- 438 MB
- SHA256:
- a9cae12287fbd773ee0b609ea86acf474e626d4fff1e46ae4b679c738a1aeefd
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