Instructions to use Jeevesh8/bert_ft_cola-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-64")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-64") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-64") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e3de963775f2f06270b2883eb544d5e3be4dde59bde11ade0637395838c1040
- Size of remote file:
- 438 MB
- SHA256:
- 6b2178ef57aa73aab9d1cff1bfa3f7321c360a48259c4766cd148aa5bcc9e83d
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