Text Classification
Transformers
PyTorch
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use henryscheible/stereoset_trainer_roberta-base_finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use henryscheible/stereoset_trainer_roberta-base_finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="henryscheible/stereoset_trainer_roberta-base_finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("henryscheible/stereoset_trainer_roberta-base_finetuned") model = AutoModelForSequenceClassification.from_pretrained("henryscheible/stereoset_trainer_roberta-base_finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 15e51f3eca3d66050160db2b89b33438ef371fbeaf26e9643c351f11acb075fa
- Size of remote file:
- 499 MB
- SHA256:
- b31047ba4b96c7d48255ef713c1fb8e99a7706a9b46896a4c34660daba574b59
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