Filtering Common Crawl through a database-driven index scan and range-request WARC downloads yields large low-resource-language corpora, and QLoRA fine-tuning on the Amharic subset reduces perplexity and slightly improves few-shot QA for XGLM.
In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 11682–11703, Toronto, Canada
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UnifiedCrawl: Aggregated Common Crawl for Affordable Adaptation of LLMs on Low-Resource Languages
Filtering Common Crawl through a database-driven index scan and range-request WARC downloads yields large low-resource-language corpora, and QLoRA fine-tuning on the Amharic subset reduces perplexity and slightly improves few-shot QA for XGLM.