Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use sgugger/distilbert-base-uncased-finetuned-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/distilbert-base-uncased-finetuned-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/distilbert-base-uncased-finetuned-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/distilbert-base-uncased-finetuned-cola") model = AutoModelForSequenceClassification.from_pretrained("sgugger/distilbert-base-uncased-finetuned-cola") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4f6d320275f88a8d62c81e1877650347762f15712e8c3497e2f32fc18106854d
- Size of remote file:
- 2.93 kB
- SHA256:
- 0bdcbcd11e5955454a4ee7b7cfa3557ca29f2c210ef9de309d7723d16bdca2b3
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