lightblue/DeepSeek-R1-Distill-Qwen-7B-Japanese is a 7.6 billion parameter language model developed by Lightblue, fine-tuned from deepseek-ai/DeepSeek-R1-Distill-Qwen-7B. This model is specifically optimized for Japanese language output in reasoning tasks, addressing inconsistencies found in the original DeepSeek R1 models. It reliably produces Japanese responses, making it suitable for applications requiring accurate Japanese reasoning.
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Model Overview
lightblue/DeepSeek-R1-Distill-Qwen-7B-Japanese is a 7.6 billion parameter model developed by Lightblue, derived from deepseek-ai's DeepSeek-R1-Distill-Qwen-7B. The primary goal of this model is to provide consistent and accurate Japanese language output for reasoning tasks, a common challenge with the original DeepSeek R1 models which often output English or Chinese when prompted in Japanese.
Key Capabilities & Differentiators
- Reliable Japanese Output: Specifically fine-tuned to ensure responses are consistently in Japanese, particularly within
<think>sections for reasoning. - Enhanced Reasoning Accuracy: Achieves 70% answer accuracy on the SakanaAI/gsm8k-ja-test_250-1319 dataset with a repetition penalty of 1.1, outperforming the base DeepSeek-R1-Distill-Qwen-7B.
- High Japanese
<think>Section Validity: Demonstrates 98% valid Japanese<think>sections on SakanaAI/gsm8k-ja-test_250-1319 and 94% on the more complex DeL-TaiseiOzaki/Tengentoppa-sft-reasoning-ja benchmark.
Usage Recommendations
For optimal performance, it is recommended to use a sampling temperature between 0.5-0.7 and set repetition_penalty to 1.1 or higher to mitigate potential self-repetition. The model was trained on a custom dataset created by translating English reasoning prompts to Japanese and filtering for valid Japanese <think> sections.