Text Classification
Transformers
PyTorch
TensorBoard
Safetensors
English
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use sgugger/bert-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgugger/bert-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sgugger/bert-finetuned-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sgugger/bert-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("sgugger/bert-finetuned-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2c903ce9d1c8e7fa54ae7eb9a0ccccc9e0023daf75bfda37f54f5e12f627f06c
- Size of remote file:
- 2.8 kB
- SHA256:
- 151cdca9dff48a6afefccb63b9dc83843a5a1f93050673d5a133ac22a11db41a
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