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:
- 52fd92ff877318197f861a5faf0da308d64ebe2585370a5887f834b60ecc1e91
- Size of remote file:
- 499 MB
- SHA256:
- f4c0725f447cf5e1ca73e09c620de2cf9860b8aa994b973a598b2cca0d6f85b4
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