divaspoudel/iol-div-1p5b
divaspoudel/iol-div-1p5b is an instruction-tuned 1.54 billion parameter causal language model from the Qwen2.5 series, developed by Qwen Team. It features a transformer architecture with a 32,768 token context length and improved capabilities in coding, mathematics, and instruction following. This model excels at generating long texts, understanding structured data, and producing structured outputs like JSON, with multilingual support for over 29 languages.
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Overview
divaspoudel/iol-div-1p5b is an instruction-tuned model from the Qwen2.5 series, developed by the Qwen Team. This 1.54 billion parameter causal language model builds upon the Qwen2 architecture, incorporating significant enhancements across various domains. It supports a substantial context length of 32,768 tokens and can generate up to 8,192 tokens.
Key Capabilities
- Enhanced Knowledge & Reasoning: Significantly improved performance in coding and mathematics due to specialized expert models.
- Instruction Following: Demonstrates better adherence to instructions and is more resilient to diverse system prompts, aiding in role-play and chatbot conditioning.
- Long Text Generation: Capable of generating extended texts exceeding 8K tokens.
- Structured Data Handling: Improved ability to understand structured data, such as tables, and generate structured outputs, particularly JSON.
- Multilingual Support: Offers support for over 29 languages, including Chinese, English, French, Spanish, and more.
Good For
- Applications requiring strong instruction following and structured output generation.
- Tasks involving code generation or mathematical problem-solving.
- Chatbots and agents needing resilience to varied system prompts and role-play implementation.
- Use cases demanding long-context understanding and multilingual text processing.