kyujinpy/Kosy-platypus2-13B-v5
kyujinpy/Kosy-platypus2-13B-v5 is a 13 billion parameter Llama 2-based model developed by Kyujin Han, fine-tuned using the NEFTune method for improved performance. This model is specifically optimized for Korean language tasks, leveraging a ko-en-llama2-13b base and the KOpen-platypus dataset. It demonstrates competitive performance on Korean LLM benchmarks, particularly in areas like Ko-CommonGen V2.
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Model Overview
kyujinpy/Kosy-platypus2-13B-v5, also known as Kosy🍵llama, is a 13 billion parameter language model developed by Kyujin Han. It is built upon the hyunseoki/ko-en-llama2-13b base model and fine-tuned using the NEFTune method, which incorporates noisy embedding fine-tuning. The training utilized the kyujinpy/KOpen-platypus combined dataset.
Key Capabilities
- Korean Language Proficiency: Optimized for Korean language understanding and generation, as evidenced by its performance on various Ko-LLM benchmarks.
- NEFTune Integration: Leverages the NEFTune method, which can be explored further via the associated KoNEFTune GitHub repository.
- Benchmark Performance: Achieves an average score of 46.31 on the KO-LLM leaderboard, with notable scores in Ko-CommonGen V2 (46.16) and Ko-HellaSwag (54.54) for its v3 iteration.
Good For
- Korean NLP Applications: Ideal for tasks requiring strong performance in the Korean language.
- Research on NEFTune: Provides a practical example of NEFTune application in a large language model context.
- Comparative Analysis: Useful for comparing performance against other Korean LLMs, particularly those listed on the KO-LLM leaderboard.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.