Text Classification
Transformers
Safetensors
deberta
deberta-v3
multiple-choice
question-answering
awp
Instructions to use a-01a/QSolver_Encoder_V2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use a-01a/QSolver_Encoder_V2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="a-01a/QSolver_Encoder_V2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("a-01a/QSolver_Encoder_V2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download fold_2/tokenizer.json from a-01a/QSolver_Encoder_V2: direct link, hf CLI and curl.
- Browser
- Download file 8.34 MB
-
https://huggingface.co/a-01a/QSolver_Encoder_V2/resolve/main/fold_2/tokenizer.json
- Command line
-
hf download hf://a-01a/QSolver_Encoder_V2/fold_2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/a-01a/QSolver_Encoder_V2/resolve/main/fold_2/tokenizer.json
8.34 MB
File too large to display, you can check the raw version instead.