Across Arabic, English, and Kannada benchmarks, 4-bit and 8-bit quantization preserves most accuracy while aggressive pruning degrades larger multilingual models more than smaller ones.
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Towards Inclusive NLP: Assessing Compressed Multilingual Transformers across Diverse Language Benchmarks
Across Arabic, English, and Kannada benchmarks, 4-bit and 8-bit quantization preserves most accuracy while aggressive pruning degrades larger multilingual models more than smaller ones.