YanoljaNEXT-EEVE-Instruct-7B-v2-Preview Overview
This model is a 7.6 billion parameter instruction-following large language model, developed by yanolja and derived from Qwen2.5-7B. It has been specifically enhanced for Korean language understanding and generation through significant vocabulary expansion, adding 6,257 Korean tokens. A key differentiator is its hybrid nature, allowing users to optionally activate a step-by-step reasoning process using <think> tags before the model provides its final answer, which is particularly useful for complex tasks like math, coding, and detailed translation.
Key Capabilities
- Enhanced Korean Language: Optimized for Korean understanding and generation due to expanded vocabulary.
- Step-by-Step Reasoning: Supports explicit reasoning processes for complex problem-solving.
- Specialized Translation: Includes a detailed prompt structure for high-quality English-to-Korean translation.
- General Instruction Following: Capable of handling a wide range of conversational and instructional prompts.
Training and Limitations
The model was fine-tuned using a combination of datasets, including distilled data from DeepSeek-R1, HuggingFaceTB/smoltalk, HuggingFaceH4/ultrafeedback_binarized, and the AI Hub Korean Conversation Summary dataset. As a "Preview" release, it may have unoptimized performance, bugs, and is subject to general LLM limitations such as factual inaccuracies (hallucinations) and potential biases. Quantitative evaluation results are pending.