Text Classification
Transformers
PyTorch
TensorBoard
English
bert
generated from trainer
text-embeddings-inference
Instructions to use minseok0809/bert-base-uncased-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minseok0809/bert-base-uncased-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minseok0809/bert-base-uncased-finetuned-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minseok0809/bert-base-uncased-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("minseok0809/bert-base-uncased-finetuned-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9e9117afec590502fd248dd97ffaaa99a31b59a5d810123ccb456234b6e6f174
- Size of remote file:
- 438 MB
- SHA256:
- 8ff2ac6e929fc02924c640ecd79ecf844ff2e8cc19e57468f44c859cb8f7fe0e
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