Saxo/Linkbricks-Horizon-AI-Japanese-Base-32B
Saxo/Linkbricks-Horizon-AI-Japanese-Base-32B is a 32.8 billion parameter language model developed by Linkbricks, based on the Qwen/QwQ-32B-Preview architecture. It has undergone continued pre-training, supervised fine-tuning, and DPO specifically to enhance its Japanese language capabilities, utilizing 20 million Japanese news and wiki corpora. This model excels in high-dimensional analysis of customer reviews and social posts, coding, writing, mathematics, and logical reasoning, supporting a 128k context window and function calling.
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Overview
Saxo/Linkbricks-Horizon-AI-Japanese-Base-32B is a 32.8 billion parameter language model developed by Yunsung Ji (Saxo), a data scientist at Linkbricks, an AI and big data analytics company. This model is built upon the Qwen/QwQ-32B-Preview base model and has undergone extensive continued pre-training (CPT), supervised fine-tuning (SFT), and Direct Preference Optimization (DPO) with a focus on Japanese language enhancement. Approximately 25% of its parameters were fine-tuned using 8 H100-80G GPUs.
Key Capabilities
- Japanese Language Enhancement: Trained on 20 million Japanese news and wiki corpora, making it highly proficient in Japanese.
- Multilingual Cross-Learning: Incorporates Japanese, Korean, Chinese, and English cross-training data for various tasks.
- Advanced Analytical Skills: Enhanced for high-dimensional analysis of customer reviews and social posts.
- Coding and Writing: Strong capabilities in code generation and creative writing.
- Mathematical and Logical Reasoning: Designed to handle complex mathematical problems and logical decision-making.
- Extended Context Window: Supports a 128k context window, allowing for processing longer inputs.
- Function Calling: Includes support for function and tool calling.
Good for
- Applications requiring strong Japanese language understanding and generation.
- Analyzing customer feedback and social media data in a high-dimensional context.
- Tasks involving coding, creative writing, and content generation.
- Solving complex mathematical and logical reasoning problems.
- Use cases benefiting from a large context window for detailed analysis.