README.md

---
language:
- en
- tr
license: bigcode-openrail-m
tags:
- stm32
- embedded
- code-generation
- hal
- firmware
base_model: bigcode/starcoder2-3b
datasets:
- custom-stm32-dataset
metrics:
- accuracy
model-index:
- name: starcoder2-stm32-turkish
  results:
  - task:
      type: text-generation
    metrics:
    - type: accuracy
      value: 85
      name: Test Accuracy (20 realistic projects)
---

# STM32 Code Generator - Turkish Fine-tuned StarCoder2-3B

## Model Özeti

Bu model, **bigcode/starcoder2-3b** temel alınarak **55,000 STM32 kod örneği** ile fine-tune edilmiştir. 
STM32F4 serisi için HAL kütüphanesi kullanan gömülü sistem kodu üretir.

## Performans

- **Test Sonucu:** 17/20 (%85) başarı oranı
- **V1 Model:** 6/20 (%30) → **V2 Model:** 17/20 (%85)
- **İyileşme:** +%55

### Test Senaryoları:
- ✅ ADC okuma ve işleme
- ✅ PWM motor kontrolü
- ✅ UART iletişim
- ✅ I2C/SPI protokolleri
- ✅ Timer interrupt'lar
- ✅ DMA kullanımı
- ✅ Watchdog timer
- ✅ Multi-sensor sistemler

## Kullanım
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
from peft import PeftModel
import torch

print("🔄 Model yükleniyor...")

base_model = AutoModelForCausalLM.from_pretrained(
    "bigcode/starcoder2-3b",
    torch_dtype=torch.float16,  
    device_map="auto"
)

model = PeftModel.from_pretrained(base_model, "MuratKomurcu/starcoder2-stm32-turkish")
tokenizer = AutoTokenizer.from_pretrained("MuratKomurcu/starcoder2-stm32-turkish")

print("✅ Model hazır!")

# TEST
prompt = '''### Instruction:
Write complete STM32F401RE LED blink code with main function

### Input:
LED on PA5, blink every 1000ms, include SystemClock_Config

### Response:
'''
```

## Eğitim Detayları

- **Base Model:** bigcode/starcoder2-3b
- **Dataset Size:** 55,000 STM32 örnekleri
- **Method:** LoRA fine-tuning (QLoRA 4-bit)
- **LoRA Rank:** 64
- **Training Epochs:** 5
- **Final Validation Loss:** 0.0297
- **Hardware:** NVIDIA A100 (40GB)
- **Training Time:** ~36 saat

### Hyperparameters:
- Learning rate: 2e-4
- Batch size: 8 (effective: 32 with gradient accumulation)
- Weight decay: 0.01
- LR Scheduler: Cosine
- Warmup ratio: 0.1

## Limitasyonlar

- STM32F4 serisine odaklıdır
- HAL kütüphanesi kullanır (LL veya register-level değil)
- Bazı kompleks senaryolarda (RGB multi-channel PWM, dual button) daha az başarılı
- Türkçe açıklamalar kabul eder ancak İngilizce promptlar daha iyi sonuç verir

## Lisans

BigCode OpenRAIL-M



## Atıf
```bibtex
@misc{starcoder2-stm32-turkish,
  author = {Murat},
  title = {STM32 Code Generator - Turkish Fine-tuned},
  year = {2024},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/MuratKomurcu/starcoder2-stm32-turkish}}
}
```