kyujinpy/Kosy-platypus2-13B-v3
Kosy-platypus2-13B-v3 is a 13 billion parameter causal language model developed by Kyujin Han (kyujinpy), fine-tuned using the NEFTune method. Based on the hyunseoki/ko-en-llama2-13b architecture, this model is optimized for Korean language tasks, demonstrating improved performance on various Korean benchmarks. It is particularly suited for applications requiring robust Korean language understanding and generation.
Loading preview...
Overview
Kosy-platypus2-13B-v3 is a 13 billion parameter language model developed by Kyujin Han (kyujinpy), building upon the hyunseoki/ko-en-llama2-13b base model. This iteration, denoted as v3, leverages the NEFTune (Noisy Embedding Fine-tuning) method to enhance its performance, particularly for Korean language tasks. The model's name, Kosy🍵llama, reflects its origin (Noisy + KO + llama).
Key Capabilities & Differentiators
- NEFTune Method: Utilizes Random Noisy Embedding Fine-tuning, a technique that can be explored further via the KoNEFTune GitHub repository.
- Korean Language Optimization: Fine-tuned on the
kyujinpy/KOpen-platypuscombined dataset, focusing on improving Korean language understanding and generation. - 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-MMLU (43.38), indicating strong performance across various Korean benchmarks compared to previous versions.
Use Cases
This model is well-suited for applications requiring advanced Korean language processing, such as:
- Korean text generation and summarization
- Korean-centric question answering systems
- Research and development in Korean natural language processing, especially for exploring the impact of NEFTune.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.