Instructions to use aomar85/StanceNakba-EXP4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/StanceNakba-EXP4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/StanceNakba-EXP4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/StanceNakba-EXP4") model = AutoModelForSequenceClassification.from_pretrained("aomar85/StanceNakba-EXP4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c344fb3e113fe5b57bd6175ca6cb485e0b37b2f93d9f54097f4890757751c168
- Size of remote file:
- 5.84 kB
- SHA256:
- 7ccf042051913e4d8b59a623939e4a05c9f0976e53b3c6dbd8b2a20e1247b1e7
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