ganchengguang/Yoko-7B-Japanese-v1
ganchengguang/Yoko-7B-Japanese-v1 is a 7 billion parameter language model fine-tuned from LLaMA2-7B, developed with contributions from Yokohama National University Mori Lab. This model is specifically optimized for improved performance in Chinese and Japanese, leveraging the Guanaco dataset for training. It is designed for chat and non-chat applications, offering enhanced linguistic capabilities for East Asian languages within a 4096-token context window.
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Model Overview
ganchengguang/Yoko-7B-Japanese-v1 is a 7 billion parameter language model built upon the vanilla LLaMA2-7B architecture. Developed with contributions from Yokohama National University Mori Lab, this model has undergone fine-tuning using QLoRA.
Key Capabilities
- Enhanced Multilingual Performance: Demonstrates improved performance specifically in Chinese and Japanese language tasks.
- Extensive Training Data: Fine-tuned on a comprehensive dataset, including 49,000 chat samples and 280,000 non-chat samples from the Guanaco dataset.
- LLaMA2 Base: Benefits from the robust foundation of the LLaMA2-7B model.
Good For
- Applications requiring strong performance in Chinese and Japanese language generation and understanding.
- Chatbot implementations and general text generation tasks in these languages.
Recommended Generation Parameters
For optimal results, consider using the following generation parameters:
- Temperature: 0.5 - 0.7
- Top P: 0.65 - 1.0
- Top K: 30 - 50
- Repeat Penalty: 1.03 - 1.17