Text Classification
Transformers
PyTorch
English
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/roberta-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/roberta-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/roberta-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/roberta-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/roberta-base-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4ae530bbea43a3603ef1cf6dc0a81e453fede51c23311a50dcd17d0de7e1dd3
- Size of remote file:
- 499 MB
- SHA256:
- f7938b88f6f408a2414fdc41230f990c06ac16e1025575f14c629d5246bcaab7
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