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Datasets:
nebhailema
/
AmaSquad

Tasks:
Question Answering
Modalities:
Text
Formats:
json
Languages:
Amharic
Size:
100K - 1M
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files Community
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@@ -30,4 +30,4 @@ Techniques such as cosine similarity (using embeddings from a fine-tuned Amharic
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  ## Citation
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  If you use this dataset, please cite:
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- Hailemariam, N. D., Guda, B., & Tefferi, T. *XLM-R Based Extractive Amharic Question Answering with AmaSQuAD*. Carnegie Mellon University Africa, Rwanda.
 
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  ## Citation
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  If you use this dataset, please cite:
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+ Hailemariam, N. D., Guda, B., & Tefferi, T. *XLM-R Based Extractive Amharic Question Answering with AmaSQuAD*. Carnegie Mellon University.