Instructions to use Jeevesh8/6ep_bert_ft_cola-39 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/6ep_bert_ft_cola-39 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/6ep_bert_ft_cola-39")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/6ep_bert_ft_cola-39") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/6ep_bert_ft_cola-39") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 11481850376c64ad443e5316d71f7740dbf04691a59f37cf40c7d56083f91791
- Size of remote file:
- 438 MB
- SHA256:
- 366cadaef93242cbb5550e19c7bc4eaf378c8422da120ba080a5f8e7f2c6ecc4
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