Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use scottstots/roberta-base-prop-16-train-set with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scottstots/roberta-base-prop-16-train-set with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="scottstots/roberta-base-prop-16-train-set")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("scottstots/roberta-base-prop-16-train-set") model = AutoModelForSequenceClassification.from_pretrained("scottstots/roberta-base-prop-16-train-set") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f351212d6e761049e7f4af4329f5bc7d76eef0491691af4a5578b24af28a1504
- Size of remote file:
- 3.31 kB
- SHA256:
- 0dd2cee8bc1c614b7876b450e3b5dbd882ac6d6c7904d21d81a917f9d0ed3a54
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