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  license: apache-2.0
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  ---
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  ![icaro](https://huggingface.co/alexsobolev/IcaroLM/resolve/main/assets/icaro.jpg)
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- **IcaroLM**, is a language model based on Qwen2 1.5B, designed for mobile efficiency, empathetic chat, and function calling.
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- This model is optimized for fast inference and low resource consumption on mobile devices, providing a seamless and responsive user experience.
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- Icaro-LM is fine-tuned for empathetic conversations and can understand and execute function calls within the conversation flow,
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- making it a versatile solution for various applications.
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- ## Key Features:
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- 1. **Mobile Efficiency**: Optimized for fast inference and low resource consumption on mobile devices.
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- 2. **Empathetic Chat**: Fine-tuned on datasets curated for empathetic and emotionally intelligent conversations.
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- 3. **Function Calling**: Can understand and execute function calls within the conversation flow.
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- ## Use Cases:
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- - Mobile chatbots and virtual assistants
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- - Emotional support applications
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- - Task automation on mobile devices
 
 
 
 
 
 
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  ## Prompt format
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  license: apache-2.0
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  ---
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  ![icaro](https://huggingface.co/alexsobolev/IcaroLM/resolve/main/assets/icaro.jpg)
 
 
 
 
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+ # IcaroLM
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+ IcaroLM is a fine-tuned and quantized version of Qwen2 1.5B, designed specifically for on-device mobile applications. By leveraging a 1.5B parameter architecture and quantization, the model is approximately **600MB** in size, making it practical for local deployment on smartphones and edge devices without requiring cloud connectivity.
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+ IcaroLM has been fine-tuned for two primary objectives: maintaining emotionally intelligent conversations and executing reliable function calls within a chat flow.
 
 
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+ ## Key Features
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+ - **Mobile-Ready Footprint:** The quantized model is roughly 600MB, allowing for efficient storage and inference on consumer mobile hardware.
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+ - **Function Calling:** Explicitly fine-tuned to understand and execute function calls, enabling local task automation and tool use.
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+ - **Empathetic Chat:** Trained on datasets curated for emotional intelligence, allowing for more natural and supportive interactions compared to base models.
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+
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+ ## Use Cases
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+
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+ - **Mobile Assistants:** Local chatbots that can perform actions on the device (via function calling) without sending data to the server.
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+ - **Emotional Support Apps:** Companion applications requiring a more empathetic and nuanced conversational tone.
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+ - **Edge Automation:** Task-oriented agents that need to run locally with low latency.
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  ## Prompt format
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