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Lego-MT/Parallel_Dataset

Dataset Sources Paper: LegoMT2: Selective Asynchronous Sharded Data Parallel Training for Massive Neural Machine Translation Link: https://aclanthology.org/2025.findings-acl.1200.pdf Repository: https://github.com/CONE-MT/CONE

sourceHugging Facemitupdated 1y agoView on Hugging Face
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1{"src_lang": "ber", "tgt_lang": "shy", "source": "Aɣrum yeqqur w-amen semḍen.", "target": "Aɣrum yeqqur amen semḍen."}2{"src_lang": "en", "tgt_lang": "shy", "source": "Good afternoon", "target": "Timdiwin"}3{"src_lang": "en", "tgt_lang": "shy", "source": "Good Night", "target": "Iḍ Amegaz"}4{"src_lang": "en", "tgt_lang": "shy", "source": "It's a beautiful weather today", "target": "Aflu n wassa yegrez"}5{"src_lang": "en", "tgt_lang": "shy", "source": "The sky is clear, but take the umbrella with you, it might rain", "target": "Ajenna yesraw macan awi idek tasiwant agella mammek iteççat tmetna"}6{"src_lang": "en", "tgt_lang": "shy", "source": "Where is she ?", "target": "Mani tella ?"}7{"src_lang": "en", "tgt_lang": "shy", "source": "What do you want ?", "target": "Metta taxsed ?"}8{"src_lang": "en", "tgt_lang": "shy", "source": "What does she want ?", "target": "Metta taxs ?"}9{"src_lang": "en", "tgt_lang": "shy", "source": "What do they want ?", "target": "Metta a-xsen ?"}10{"src_lang": "en", "tgt_lang": "shy", "source": "Eat bread.", "target": "Ačč aɣrum!"}11{"src_lang": "en", "tgt_lang": "shy", "source": "Snow falls every day.", "target": "Adfel yiččet Akkes."}12{"src_lang": "en", "tgt_lang": "shy", "source": "Snow falls on the mountains.", "target": "Aḍfel yi-ččet ḍeg iḍurar."}13{"src_lang": "en", "tgt_lang": "shy", "source": "Eat bread and drink water.", "target": "Ačč aɣrum tsud amen."}14{"src_lang": "en", "tgt_lang": "shy", "source": "Bread is dry, water is cold.", "target": "Aɣrum yeqqur amen semḍen."}15{"src_lang": "en", "tgt_lang": "shy", "source": "Bread is dry, water is cold", "target": "Aɣrum yeqqur amen semḍen."}16