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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c8ec98d8cfc507ae9889ebf5332a133d9628b4b8d66c90f612b5f0cc4e9789fd
- Size of remote file:
- 3.38 kB
- SHA256:
- 65e75f9c843713cd234979516b4ebb400db6b13ec1aad6bd4cc22bfb46364e82
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