Hugging Face Overview
Overview
unsloth/Qwen2.5-0.5B-Instruct is a 0.49 billion parameter instruction-tuned causal language model from the Qwen2.5 series, developed by Qwen. It is built on a transformer architecture utilizing RoPE, SwiGLU, RMSNorm, Attention QKV bias, and tied word embeddings, with a full context length of 32,768 tokens and generation capability up to 8,192 tokens. This model represents an advancement over Qwen2, focusing on enhanced performance across several key areas.
Key Capabilities
- Expanded Knowledge & Skills: Significantly improved capabilities in coding and mathematics, leveraging specialized expert models.
- Instruction Following: Enhanced ability to follow instructions and generate structured outputs, particularly JSON.
- Long Text Generation: Improved performance in generating texts over 8,000 tokens.
- Structured Data Understanding: Better comprehension of structured data, such as tables.
- Multilingual Support: Supports over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic.
- Robustness: More resilient to diverse system prompts, aiding in role-play and chatbot condition-setting.
Good For
- Applications requiring strong instruction following and structured output generation.
- Tasks involving coding and mathematical reasoning, especially in a multilingual context.
- Chatbot implementations needing robust role-play and prompt resilience.
- Scenarios demanding long-context understanding and generation up to 8K tokens.