alexsobolev/IcaroLM
IcaroLM by alexsobolev is a fine-tuned and quantized version of Qwen2 1.5B, specifically optimized for on-device mobile applications. With approximately 1.5 billion parameters and a quantized size of 600MB, it is designed for efficient local deployment on smartphones and edge devices. This model excels at maintaining emotionally intelligent conversations and executing reliable function calls within a chat flow, making it ideal for mobile assistants and emotional support applications.
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IcaroLM: Mobile-Optimized LLM for Empathetic Chat and Function Calling
IcaroLM, developed by alexsobolev, is a specialized fine-tuned and quantized version of the Qwen2 1.5B model. It is engineered for efficient on-device deployment, making it highly suitable for mobile and edge applications. The model's quantization reduces its footprint to approximately 600MB, enabling local inference without cloud dependency.
Key Capabilities
- Mobile-Ready Footprint: Optimized for consumer mobile hardware with a compact 600MB size.
- Function Calling: Explicitly fine-tuned to understand and execute function calls, facilitating local task automation and tool use.
- Empathetic Chat: Trained on datasets focused on emotional intelligence for more natural and supportive conversational interactions.
Good for
- Mobile Assistants: Creating local chatbots capable of performing device-specific actions via function calls.
- Emotional Support Apps: Developing companion applications that require nuanced and empathetic conversational tones.
- Edge Automation: Implementing task-oriented agents that operate locally with minimal latency.