Text Classification
Transformers
PyTorch
TensorBoard
deberta
Generated from Trainer
Eval Results (legacy)
Instructions to use Tomor0720/deberta-base-finetuned-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tomor0720/deberta-base-finetuned-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Tomor0720/deberta-base-finetuned-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Tomor0720/deberta-base-finetuned-sst2") model = AutoModelForSequenceClassification.from_pretrained("Tomor0720/deberta-base-finetuned-sst2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 492f0df1de9ad9d711daf991fab2f66966425583694a6c3eca9acc1ab1138f63
- Size of remote file:
- 557 MB
- SHA256:
- efd422a64dc0350af72849daa5ed0eedd6e8b3d12b0411ecfba0135216be4145
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