GAI-LLM/ko-en-llama2-13b-mixed-v2
GAI-LLM/ko-en-llama2-13b-mixed-v2 is a 13 billion parameter auto-regressive language model developed by Donghoon Oh, Hanmin Myung, and Eunyoung Kim (SK C&C G.AI Eng), based on the LLaMA2 transformer architecture. This model is specifically fine-tuned for mixed Korean and English language processing, leveraging a combination of Open Korean Datasets. It is designed to excel in tasks requiring understanding and generation in both Korean and English contexts.
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Overview
GAI-LLM/ko-en-llama2-13b-mixed-v2 is a 13 billion parameter auto-regressive language model built upon the LLaMA2 transformer architecture. Developed by Donghoon Oh, Hanmin Myung, and Eunyoung Kim from SK C&C G.AI Eng, this model is specifically designed for mixed Korean and English language processing.
Key Capabilities
- Bilingual Proficiency: Optimized for understanding and generating text in both Korean and English.
- Llama2 Base: Leverages the robust Llama2 architecture for strong foundational language capabilities.
- Specialized Training: Fine-tuned on a combination of Open Korean Datasets, including Kopen-platypus, Everythinglm v2, koalpaca_v1.1, and koCoT2000, using A100 GPUs.
Use Cases
This model is particularly well-suited for applications requiring:
- Korean-English Translation: Tasks involving translation or cross-lingual understanding between Korean and English.
- Bilingual Content Generation: Creating text in either Korean or English, or mixed-language content.
- Research and Development: As a base for further fine-tuning on specific Korean-English NLP tasks.
Performance can be tracked on the Open KO-LLM LeaderBoard.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.