Text Classification
Transformers
PyTorch
English
bert
Generated from Trainer
bert-base-uncased
fp32
Eval Results (legacy)
text-embeddings-inference
Instructions to use Intel/bert-base-uncased-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Intel/bert-base-uncased-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Intel/bert-base-uncased-mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Intel/bert-base-uncased-mrpc") model = AutoModelForSequenceClassification.from_pretrained("Intel/bert-base-uncased-mrpc", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Update README.md
Verified signatureAdded more explanation of dataset and base model bibliographic information Added sections for # Related work on QuantizationAwareTraining # Ethical Considerations and Limitations # Caveats and Recommendations # Disclaimer # BibTeX entry and citation info9fa15f9
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Update ReadMe.md (#5)
Verified signature- Update ReadMe.md (398cc700c8f517ea4728d2658023fa0ca0b6c8d0) Co-authored-by: bob chesebrough <Chesebrough@users.noreply.huggingface.co>2c99cf8
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Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (#2)
- Add verifyToken field to verify evaluation results are produced by Hugging Face's automatic model evaluator (79fae78d284e9582dec28ac92747ce5f05242473) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>cc89a47
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Add evaluation results on the mrpc config of glue (#1)
- Add evaluation results on the mrpc config of glue (84e0cd37eda4053e63975ff318fcc4b944484493) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>1b9f67b
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remove result.json files
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upload fine-tuned model
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