Extracting an optimized Arduino Tool-Calling Subnet from the SmolLM2 model.
I want a plan for extracting a subnet from the SmolLM2 model that is reliable for Arduino-Tool calling: Intelligently Read/Activate pins of the arduino based on text input. For example, call a arduino tool for implementing "if the answer is "yes", turn on the red LED lights one hundred times at interval of 400 miliseconds" The arduino tool can leverage existing text-based arduino control libraries used for serial communication.
Model
34.2s
Project Plan: SmolLM2 Subnet for Arduino Tool Calling
This plan focuses on extracting a SmolLM2 subnet specifically designed for reliable Arduino tool calling based on natural language instructions.
Target Arduino Boards: Arduino Portenta H7 is the preferred target due to its more powerful processor and greater memory capacity. Other powerful boards might be feasible with extensive optimization.
Phase 1: Subnet Extraction and Specialization
Task 1.1: Define a Custom Arduino Control Vocabulary:
Description: Create a specialized vocabulary tailored for Arduino control commands. This vocabulary should include keywords related to:
Digital I/O (e.g., pinMode, digitalWrite, HIGH, LOW)
Analog I/O (e.g., analogRead, analogWrite)
Timing (e.g., delay, millis)
Specific peripherals (e.g., Serial, LED, Servo)
Control flow (e.g., if, else, for, while)
Details: Balance the vocabulary size with the available memory on the Arduino. Prioritize commonly used commands. This custom vocabulary will be crucial for efficient tokenization and generation of Arduino code.
Deliverables: A defined vocabulary list and corresponding token mapping.
Task 1.2: Fine-tune a SmolLM2 Subnet on Arduino Control Data:
Description: Instead of simply extracting a subnet, fine-tune a small SmolLM2 subnet on a dataset of natural language instructions paired with corresponding Arduino code. This dataset should cover a range of control tasks relevant to your application.
Details: Create a dataset of example pairs like:
Instruction: "Blink the blue LED five times."
Arduino Code: for (int i = 0; i < 5; i++) { digitalWrite(LED_BUILTIN, HIGH); delay(500); digitalWrite(LED_BUILTIN, LOW); delay(500); }
Use a relatively small subnet (e.g., a heavily pruned version of the 134M model) to make it feasible for deployment on the Arduino. Quantization (Task 1.3) will further reduce the memory footprint.
Deliverables: A fine-tuned SmolLM2 subnet specialized for Arduino tool calling.
Task 1.3: Quantize the Fine-tuned Subnet: (Same as in previous plans)
Phase 2: Arduino Development Environment Setup
Task 2.1: Integrate a Lightweight Interpreter/Code Executor:
Description: Instead of directly compiling C++ on the Arduino, integrate a lightweight interpreter or a simplified code executor capable of running the Arduino control vocabulary commands.
Details: This could be a custom-built interpreter or a simplified version of an existing Arduino scripting language. This approach avoids the complexities of a full C++ compiler on the Arduino. The interpreter should be designed to efficiently execute the limited vocabulary commands.
Deliverables: An integrated interpreter or code executor for Arduino control commands.
Phase 3: Implementation and Integration
Task 3.1: Specialized Tokenization:
Description: Implement a tokenizer that uses the custom Arduino control vocabulary.
Details: The tokenizer should efficiently convert natural language instructions into tokens that the fine-tuned subnet can process.
Task 3.2: Inference and Code Generation:
Description: Implement the inference loop to process input instructions, tokenize them using the custom tokenizer, run inference using the fine-tuned subnet, and generate the corresponding Arduino control code.
Details: The generated code should be in a format understandable by the integrated interpreter/executor.
Task 3.3: Interpreter/Executor Integration:
Description: Integrate the interpreter/executor to execute the generated Arduino code. Ensure error handling and robust communication between the inference engine and the interpreter.
Phase 4: Testing and Optimization (Similar to previous plans)
Example Scenario and Arduino Code Generation:
Instruction: "If the answer is "yes", turn on the red LED lights one hundred times at an interval of 400 milliseconds."
Generated Arduino Code (Simplified Interpreter Format):
IF (answer == "yes") {
FOR (i = 0; i < 100; i++) {
digitalWrite(redLED, HIGH);
delay(400);
digitalWrite(redLED, LOW);
delay(400);
}
}
Use code with caution.
This plan focuses on specializing a smaller SmolLM2 subnet for a specific task, Arduino tool calling. By using a custom vocabulary and a lightweight interpreter, we can make this application feasible on a resource-constrained microcontroller like the Arduino Portenta H7. Fine-tuning a subnet rather than just extracting one improves reliability for this targeted task. Remember to prioritize memory efficiency and performance optimization throughout the development process.