Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use JeremiahZ/roberta-base-cola with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JeremiahZ/roberta-base-cola with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JeremiahZ/roberta-base-cola")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JeremiahZ/roberta-base-cola") model = AutoModelForSequenceClassification.from_pretrained("JeremiahZ/roberta-base-cola") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9c843ccb653fdb90b95bc73ddece2871cc4d7b3e0f813a596893f93a20f5ad2b
- Size of remote file:
- 499 MB
- SHA256:
- a6bb225e1f30bd6a73a571cc7a4b656ee69a42b37c13ea052546971fed4bda9d
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