Text Classification
Transformers
Safetensors
deberta
deberta-v3
multiple-choice
question-answering
awp
Instructions to use dahaludba/QSolver_Encoder_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dahaludba/QSolver_Encoder_V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dahaludba/QSolver_Encoder_V2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("dahaludba/QSolver_Encoder_V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f839fece8b08f1ec09b97484f1a4b18dec1d389f1296901b0e934eed7892f944
- Size of remote file:
- 5.27 kB
- SHA256:
- 3b49d3f8ecf9145e8c3c8af382c1736858730a50204713dfff9ce9590e7f5d5a
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