Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use autoevaluate/glue-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use autoevaluate/glue-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="autoevaluate/glue-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("autoevaluate/glue-mrpc") model = AutoModelForSequenceClassification.from_pretrained("autoevaluate/glue-mrpc") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b048cdd93c31a28ffd08da1f52d674302cbf5ab97a1df70c9ff6898b5ebffd33
- Size of remote file:
- 268 MB
- SHA256:
- b6691a3a016ed5d656fd308e48d02ff8617bb12675519324e939acf9cd7865f1
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