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:
- e7f6982794e5919417f8c02f01e55f862b311b13429c90311de8747665ca62b6
- Size of remote file:
- 1.36 GB
- SHA256:
- 5ea86c2834bcd489c40766050836b1b43ef3d90ba1a23e9777889f10b788f6cd
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