Instructions to use Jeevesh8/bert_ft_cola-37 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-37 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-37")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-37") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-37") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba95cb60ce3011479966db20fbcf074d22acb698a6f6ea0a5c429c4ec78abc2a
- Size of remote file:
- 438 MB
- SHA256:
- 3a13aac37e03c8eedf4b4aa48667e07681e6ae3e4020ce1ae7d4b4ccb87825ff
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