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:
- cedab311c51fc6e0366f62d86d64a6115ab89e248718cd3fe9164f165020c8cc
- Size of remote file:
- 1.36 GB
- SHA256:
- 96f083b4e39b0bb116b0d82325122b2bd6e49723c8d80e3586d683cbfc44a06a
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