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:
- c349c44e1b897cd6b93a6f92c1ef082032530bd91df6f3ecc8d3309ca65e0342
- Size of remote file:
- 3.45 kB
- SHA256:
- 728bdc710fd3aa9ca709977a336c5675d81b360a23b1805e99c6a14cf0d07928
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