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")# pip install -U transformers accelerate # 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
Commit History
-
Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (f22f8259d4bf48694eac9fdc3037ca7f23a03107) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>b85afb4
-
Add evaluation results on the mrpc config of glue (#1)
- Add evaluation results on the mrpc config of glue (bb622454708170d54bf7b074160a3e4120b9feb8) Co-authored-by: Evaluation Bot <autoevaluator@users.noreply.huggingface.co>ddabe72
-
End of training
947a164 -
Training in progress, epoch 3
a626e2c -
Training in progress, epoch 2
cd1069c -
Training in progress, epoch 1
695652f -
initial commit
3239d45