| --- |
| license: apache-2.0 |
| base_model: Qwen/Qwen2.5-Coder-14B-Instruct |
| pipeline_tag: text-generation |
| tags: |
| - code-generation |
| - secure-coding |
| - patch-generation |
| - rocm |
| - qwen2.5-Coder |
| - amd-hackathon |
| - Axolotl |
| - LoRA(PEFT) |
| --- |
| |
| # 🔧 Security Builder Model (14B) |
|
|
| Fine-tuned Qwen2.5-Coder-14B-Instruct khusus untuk **generasi patch keamanan & penulisan kode aman**. Melengkapi Auditor model dengan mengubah laporan kerentanan menjadi kode perbaikan yang production-ready. |
|
|
| ## 🚀 Quick Load |
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| import torch |
| |
| model_id = "lablab-ai-amd-developer-hackathon/security-builder-14b" |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto") |
| |
| ### 💬 Example Usage (JSON Mode) |
| messages = [ |
| {"role": "user", "content": "Fix the buffer overflow and return JSON with keys: fixed_code, explanation, cwe_mitigated."} |
| ] |
| prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
| inputs = tokenizer(prompt, return_tensors="pt").to(model.device) |
| |
| with torch.no_grad(): |
| output = model.generate(**inputs, max_new_tokens=512, temperature=0.1) |
| |
| import json |
| print(json.loads(tokenizer.decode(output[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))) |
| ``` |
| #### 🛠️ Technical Specifications |
|
|
| | Parameter | Value | |
| | :--- | :--- | |
| | **Base Model** | Qwen2.5-Coder-14B-Instruct | |
| | **Fine-tuning** | LoRA (r=64, alpha=128, dropout=0.05) | |
| | **Training Data** | Custom secure coding & patch dataset | |
| | **Epochs** | 3 | |
| | **Precision** | float16 (ROCm-optimized) | |
| | **Format** | Safetensors (6 shards, ~28GB) | |
| | **VRAM Required** | ~38-42 GB | |
|
|
| ##### 🖥️ ROCm & Hardware Optimization |
| Dioptimalkan untuk AMD Instinct MI300X / ROCm 7.0. Disarankan set env var berikut sebelum inference: |
| export HSA_OVERRIDE_GFX_VERSION=11.0.0 |
| export PYTORCH_HIP_ALLOC_CONF=expandable_segments:False |
| |
| ###### 🔌 API Integration |
| Designed for CI/CD integration. Gunakan response_format={"type":"json_object"} untuk parsing otomatis patch & metadata keamanan. |
| |
| ###### 📜 License & Credits |
| Apache 2.0. Developed for the AMD Developer Hackathon 2026. |
| |
| |
