Text Classification
Transformers
PyTorch
English
xlm-roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/xlm-roberta-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/xlm-roberta-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/xlm-roberta-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/xlm-roberta-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/xlm-roberta-base-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b1539e245713a3a4e20891d8899ad64c6af002d48d9b6c844868c203ed9a7c69
- Size of remote file:
- 3.06 kB
- SHA256:
- c47d6e9df27f8913e6cff0c53a0a28b17435595e30ddce3cdfb5780dc07518ab
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