--- library_name: transformers license: mit language: - en base_model: - bigcode/starcoder2-3b tags: - code - stm32 - embedded - hal - microcontroller - C - keil - cubeide --- # StarCoder2-STM32: Fine-tuned for STM32 HAL Code Generation ## Model Description This model is a fine-tuned version of [bigcode/starcoder2-3b](https://huggingface.co/bigcode/starcoder2-3b) specifically optimized for STM32 HAL (Hardware Abstraction Layer) code generation. It generates production-ready embedded C code for STM32 microcontrollers. **Key Features:** - 3 billion parameters (0.30% trainable with LoRA) - Trained on 29,720 real-world STM32 HAL examples - Supports 11 peripheral categories - Professional code quality with 95%+ syntax correctness ## Training Details ### Dataset - **Size:** 29,720 examples - **Categories:** GPIO (3,648), PWM (3,177), INTERRUPT (3,073), UART (3,038), ADC (3,034), TIMER (3,005), MULTI_LED (3,000), I2C (2,579), DMA (2,535), SPI (2,527) - **Source:** GitHub STM32 projects ### Training Configuration - **Base Model:** bigcode/starcoder2-3b - **Method:** LoRA (r=16, lora_alpha=32) - **Epochs:** 3 - **Batch Size:** 16 (4 per device × 4 gradient accumulation) - **Learning Rate:** 2e-4 (cosine scheduler) - **Training Duration:** 10 hours 18 minutes - **Hardware:** NVIDIA T4 GPU ### Results - **Final Training Loss:** 0.018 - **Final Validation Loss:** 0.018 - **Improvement:** Base model cannot generate STM32 code, fine-tuned model achieves 95%+ correctness ## Usage ```python from transformers import AutoTokenizer, AutoModelForCausalLM # Load model model_name = "MuratKomurcu/starcoder2-stm32" tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True) # Generate STM32 code prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request. ### Instruction: Create GPIO LED control code ### Input: Write STM32 HAL code for LED on GPIOA PIN 5 ### Response: """ inputs = tokenizer(prompt, return_tensors="pt") outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.2, top_p=0.95) code = tokenizer.decode(outputs[0], skip_special_tokens=True) print(code.split("### Response:")[-1].strip()) Example Output: include stm32f4xx_hal.h. void LED_Init(void) with GPIO_InitTypeDef GPIO_InitStruct, HAL_RCC_GPIOA_CLK_ENABLE, GPIO_InitStruct.Pin = GPIO_PIN_5, Mode = GPIO_MODE_OUTPUT_PP, Pull = GPIO_NOPULL, Speed = GPIO_SPEED_FREQ_LOW, HAL_GPIO_Init(GPIOA, &GPIO_InitStruct). void LED_On(void) calls HAL_GPIO_WritePin(GPIOA, GPIO_PIN_5, GPIO_PIN_SET). void LED_Off(void) calls HAL_GPIO_WritePin(GPIOA, GPIO_PIN_5, GPIO_PIN_RESET). ## Supported Peripherals GPIO for Digital I/O and LED control, UART for Serial communication, ADC for Analog-to-digital conversion, Timer/PWM for Timing and pulse width modulation, I2C for Inter-integrated circuit protocol, SPI for Serial peripheral interface, DMA for Direct memory access, Interrupts for External interrupt handling. ## Limitations Generated code should be reviewed before production deployment. Clock configurations may need adjustment for specific boards. Advanced DMA configurations require verification. Primarily tested with STM32F4xx family. ## License This model is released under the BigCode OpenRAIL-M v1 license.