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:
- fc23fd8f4bd77f06b8b313582a25c0ad6cdab313e25f719dba904245a4ae7412
- Size of remote file:
- 2.61 kB
- SHA256:
- 7a3e4b7ede58d2ddfdb7b6a4ea624feed88d567a0d4884fc7c194b64e9f81ca0
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