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:
- d10cb75425faf407479b29d105bd811427a00937009c31bf7238758f98109897
- Size of remote file:
- 1.36 GB
- SHA256:
- b0ffa40cf55e761a03ee03dd0a18755db585a16cf21676b1a59d4498af56bb99
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