Kanana-nano-2.1b-base
| Property | Value |
|---|---|
| Parameter Count | 2.1B |
| License | CC-BY-NC-4.0 |
| Developer | Kakao Corporation |
| Model URL | huggingface.co/kakaocorp/kanana-nano-2.1b-base |
What is kanana-nano-2.1b-base?
Kanana-nano-2.1b-base is a foundational bilingual language model developed by Kakao Corporation, specifically designed to excel in both Korean and English language processing. As part of the larger Kanana model series, it represents the most compact version at 2.1B parameters, yet delivers impressive performance, particularly in Korean language tasks.
Implementation Details
The model leverages several advanced techniques to achieve compute-efficient performance, including high-quality data filtering, staged pre-training, depth up-scaling, and pruning and distillation methods. On benchmark tests, it achieves notable scores with MMLU (54.83), KMMLU (44.80), and HAERAE (77.09), demonstrating competitive performance against other models in its parameter range.
- Optimized for bilingual processing (Korean-English)
- Implements compute-efficient training techniques
- Built with high-quality data filtering
- Utilizes staged pre-training approach
Core Capabilities
- Strong performance in Korean language tasks
- Competitive English language capabilities
- Efficient compute utilization
- Versatile text generation and understanding
- Optimized for research and development purposes
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its exceptional balance between computational efficiency and performance, particularly in Korean language tasks. Despite its relatively small size, it achieves impressive results on various benchmarks, making it an excellent choice for Korean-English bilingual applications.
Q: What are the recommended use cases?
The model is well-suited for research applications, basic text generation tasks, and applications requiring balanced Korean-English language capabilities. It's particularly valuable for scenarios where computational resources are limited but bilingual performance is essential.
