Instructions to use AMR-KELEG/Sentence-ALDi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AMR-KELEG/Sentence-ALDi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AMR-KELEG/Sentence-ALDi")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AMR-KELEG/Sentence-ALDi") model = AutoModelForSequenceClassification.from_pretrained("AMR-KELEG/Sentence-ALDi") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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@@ -38,7 +38,7 @@ if __name__ == "__main__":
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s2 = "الجو حلو النهاردة"
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print(s1, round(compute_score(s1), 3)) # 0
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print(
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```
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### Model Description
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s2 = "الجو حلو النهاردة"
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print(s1, round(compute_score(s1), 3)) # 0
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print(s2, round(compute_score(s2), 3)) # 0.951
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```
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### Model Description
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