Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use fe2plus/bert-fine-tuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fe2plus/bert-fine-tuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fe2plus/bert-fine-tuned-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fe2plus/bert-fine-tuned-cola") model = AutoModelForSequenceClassification.from_pretrained("fe2plus/bert-fine-tuned-cola", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8e329858f8961585ef82f477b203867f90d4118d3a14c695548a7482e1bc7509
- Size of remote file:
- 433 MB
- SHA256:
- 2d648e7d9420775156a90e115be2e3516bbcb1fe95458bbbce766ebf69a4ad08
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