Instructions to use aomar85/StanceNakba-EXP3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/StanceNakba-EXP3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/StanceNakba-EXP3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/StanceNakba-EXP3") model = AutoModelForSequenceClassification.from_pretrained("aomar85/StanceNakba-EXP3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6427d7590fb35db7d3301948307442325177ce2acdaf6ad3429c4bebf4a89121
- Size of remote file:
- 5.84 kB
- SHA256:
- e590d089a16ac4eb43990e9d39ed244769e2a9722bdff4bb14922024762adf04
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