Instructions to use aomar85/StanceNakba-EXP7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/StanceNakba-EXP7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/StanceNakba-EXP7")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/StanceNakba-EXP7") model = AutoModelForSequenceClassification.from_pretrained("aomar85/StanceNakba-EXP7") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8679b979141aab145e755071dd72ee8eb311c6d8eaae7589b56a076dda74ceba
- Size of remote file:
- 5.2 kB
- SHA256:
- 7f0e635f412fb0411fab4d5ae5ee08e3a3d2d55f94d11f391618b9c37187ccb0
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