Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use sgugger/finetuned-bert-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/finetuned-bert-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/finetuned-bert-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/finetuned-bert-mrpc") model = AutoModelForSequenceClassification.from_pretrained("sgugger/finetuned-bert-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31c200a39b64c62fe57677b3d234ec705f362827e47334a5813a99c1a15b146b
- Size of remote file:
- 433 MB
- SHA256:
- 1c0f956fad644fb46c7d1bc8abf538cfc87af72ce55a8caa603cbc715d433254
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