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