Instructions to use Jeevesh8/bert_ft_cola-72 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/bert_ft_cola-72 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Jeevesh8/bert_ft_cola-72")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/bert_ft_cola-72") model = AutoModelForSequenceClassification.from_pretrained("Jeevesh8/bert_ft_cola-72") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2775f28689b2abf300ad050d6499059368cb112a9bed55088ac13761b603a7b4
- Size of remote file:
- 438 MB
- SHA256:
- 49fd28734f4d411fd6b8cc48c6a9c84a26b89b5a923518a9871d2e96c08e609a
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