Use Cases |
Areas: | research, evaluation of Nordic language capabilities |
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Primary Use Cases: | Research on LLMs in Nordic languages, Validation of model capabilities |
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Limitations: | Bias, Safety issues, Generation diversity, Hallucination, Possibility of harmful or inappropriate content |
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Training Details |
Data Sources: | Litteraturbanken, The Pile, Diva, PubMed, ArXiv, CodeParrot, Familjeliv, Flashback, Parlai, Pushshift.io Reddit dataset, English Math dataset from DeepMind, Swedish Math dataset, OPUS, Movie scripts, Natural Instructions, P3, Norwegian Colossal Corpus, Danish Gigaword, Icelandic Gigaword, Common Crawl, LES, Multilingual C4, OSCAR, Open Web Text, Various public Swedish website scrapes, JobTech/Arbetsförmedlingen, Wikipedia |
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Data Volume: | 1.1TB of UTF-8 encoded text containing 660M documents with a total of 320B tokens |
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Methodology: | Pretrained using a causal language modeling (CLM) objective utilizing the NeMo Megatron GPT implementation. |
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Model Architecture: | |
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