Text Classification
Transformers
PyTorch
TensorBoard
data2vec-text
Generated from Trainer
Eval Results (legacy)
Instructions to use mrm8488/data2vec-text-base-finetuned-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mrm8488/data2vec-text-base-finetuned-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mrm8488/data2vec-text-base-finetuned-mrpc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mrm8488/data2vec-text-base-finetuned-mrpc") model = AutoModelForSequenceClassification.from_pretrained("mrm8488/data2vec-text-base-finetuned-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Align label mapping with mrpc config of glue dataset (#1)
- Align label mapping with mrpc config of glue dataset (76af90faef5427e435eef58d15370c9a99e9c50b) Co-authored-by: Lewis Tunstall <lewtun@users.noreply.huggingface.co>6a12e84
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update model card README.md
b65b6a7 -
End of training
dc8245c -
Training in progress, epoch 1
158a77c -
initial commit
4cd32db