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")# 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") - Inference
- Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#8
by SFconvertbot - opened
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