TreezzZ/opd-teacher-search-7b
The TreezzZ/opd-teacher-search-7b model is an instruction-tuned Qwen2.5 causal language model developed by Qwen, featuring 7.61 billion parameters. It significantly improves upon Qwen2 with enhanced knowledge, coding, and mathematics capabilities, alongside better instruction following and long text generation. This model supports a context length of up to 131,072 tokens and is optimized for structured data understanding and multilingual applications across over 29 languages.
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Qwen2.5-7B-Instruct Overview
This model is the instruction-tuned 7.61 billion parameter version of the Qwen2.5 series, developed by Qwen. It builds upon the Qwen2 architecture, incorporating transformers with RoPE, SwiGLU, RMSNorm, and Attention QKV bias. A key feature is its substantial improvement in knowledge, particularly in coding and mathematics, achieved through specialized expert models.
Key Capabilities
- Enhanced Instruction Following: More robust and resilient to diverse system prompts, improving role-play and chatbot condition-setting.
- Long Text Generation: Capable of generating texts over 8K tokens and supports a full context length of up to 131,072 tokens, with YaRN for long text processing.
- Structured Data Handling: Significantly improved in understanding structured data like tables and generating structured outputs, especially JSON.
- Multilingual Support: Offers comprehensive support for over 29 languages, including major global languages like Chinese, English, French, Spanish, and Japanese.
Good For
- Applications requiring strong coding and mathematical reasoning.
- Chatbots and agents needing robust instruction following and role-play capabilities.
- Tasks involving long document summarization or generation.
- Processing and generating structured data, such as JSON outputs.
- Multilingual applications across a broad range of languages.