Lightweight LLM Development for Raspberry Pi 5

Project Requirement: Develop a Small and Fast LLM Model for Raspberry Pi 5

We are looking for a developer or team with expertise in AI and embedded systems to create a lightweight and efficient LLM (Language Learning Model) for a Raspberry Pi 5. The primary goal is to enable the model to process audiovisual inputs and answer questions based on provided or fed data.

Key Requirements:
1. Platform Compatibility:
• Must run efficiently on Raspberry Pi 5 hardware.
• Optimize for limited computing resources (e.g., CPU, RAM).
2. Model Features:
• Ability to process audio input (speech-to-text) and visual input (camera feed for image recognition or text extraction).
• Provide text-based answers derived from the fed data or context.
3. Performance:
• Model should be lightweight with minimal latency.
• High accuracy in understanding and generating responses based on context.
4. Input/Output Specifications:
• Audio input: Use microphone or pre-recorded audio files.
• Visual input: Accept image or video feed from the Pi camera.
• Output: Text or audio response.
5. Data Handling:
• The model should work with a pre-fed database or custom datasets provided during runtime.
6. Integration:
• Compatible with peripherals like Raspberry Pi cameras, microphones, and speakers.
• Use Python or C++ for integration with Raspberry Pi 5.
7. Preferred Frameworks:
• TensorFlow Lite, PyTorch Mobile, or similar lightweight frameworks suitable for edge devices.
8. Documentation & Support:
• Provide complete documentation for setup, deployment, and use.
• Offer basic post-delivery support for debugging and minor changes.

Deliverables:
• A fully functional and optimized LLM model compatible with Raspberry Pi 5.
• Scripts/codebase for data feeding and model training (if required).
• Integration instructions for audiovisual input/output.

Timeline: To be discussed based on your expertise and feasibility.
Budget: Please provide your proposal with cost estimation.