Instructions to use aomar85/StanceNakba-EXP2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/StanceNakba-EXP2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/StanceNakba-EXP2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/StanceNakba-EXP2") model = AutoModelForSequenceClassification.from_pretrained("aomar85/StanceNakba-EXP2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31d58ba316dc8f5be26a60cf6b57e8ec10c479de001df145298db5d8a5494660
- Size of remote file:
- 5.84 kB
- SHA256:
- 4f3994d7241f557aae836495460ba32fc7f230dd4457d6d3c86f0697ba15a479
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