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.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
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+secucoder-q4_k_m.gguf filter=lfs diff=lfs merge=lfs -text

Modelfile

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+FROM secucoder-q4_k_m.gguf
+
+PARAMETER temperature 0.1
+PARAMETER top_p 0.9
+PARAMETER num_ctx 4096
+
+SYSTEM """You are a secure Python assistant. Help identify, explain, and fix security issues in Python code. Prefer safe, practical, and production-ready solutions."""

README.md

@@ -1,3 +1,119 @@
 ---
 license: cc-by-nc-sa-4.0
+language:
+  - en
+base_model: ivitopow/secucoder
+tags:
+  - code
+  - security
+  - python
+  - gguf
+  - ollama
+  - llama-cpp
+  - cybersecurity
+  - secure-coding
+  - quantized
+task_categories:
+  - text-generation
 ---
+
+# SecuCoder — GGUF
+
+Quantized GGUF version of [SecuCoder](https://huggingface.co/ivitopow/secucoder), a fine-tuned Llama 3.1 8B Instruct model for secure Python code generation and vulnerability remediation.
+
+For full model details, training methodology, and evaluation results, see the [main model card](https://huggingface.co/ivitopow/secucoder).
+
+---
+
+## Available Files
+
+| File | Quantization | Size | Use case |
+|---|---|---|---|
+| `secucoder-Q4_K_M.gguf` | Q4_K_M | ~4.6 GB | Recommended — best balance of quality and size |
+
+---
+
+## Usage with Ollama
+
+**1. Download the Modelfile from this repo and create the model:**
+
+```bash
+ollama create secucoder -f Modelfile
+```
+
+**2. Run it:**
+
+```bash
+ollama run secucoder
+```
+
+**3. Or via API:**
+
+```bash
+curl http://localhost:11434/api/generate -d '{
+  "model": "secucoder",
+  "prompt": "Fix the security vulnerability in this Python code.\n\n```python\nname = request.args.get(\"name\")\nresp = make_response(\"Your name is \" + name)\n```\n\nCWE: CWE-079",
+  "stream": false
+}'
+```
+
+---
+
+## Usage with llama.cpp
+
+```bash
+./llama-cli \
+  -m secucoder-Q4_K_M.gguf \
+  --ctx-size 4096 \
+  --temp 0.1 \
+  --top-p 0.9 \
+  -p "You are a secure Python assistant. Fix the vulnerability in this code: ..."
+```
+
+---
+
+## Recommended Parameters
+
+| Parameter | Value |
+|---|---|
+| `temperature` | 0.1 |
+| `top_p` | 0.9 |
+| `num_ctx` | 4096 |
+| `num_predict` | 3072 |
+
+---
+
+## System Prompt
+
+```
+You are a secure Python assistant. Help identify, explain, and fix security issues in Python code. Prefer safe, practical, and production-ready solutions.
+```
+
+---
+
+## Evaluation
+
+The full SecuCoder system (Q4 + structured prompting + RAG) achieves an overall score of **77.11** vs **60.34** for the untuned Llama 3.1 8B baseline — a **+27.8% improvement** measured by weighted static analysis findings (Bandit + Semgrep).
+
+| Variant | Overall Score |
+|---|---|
+| Llama 3.1 8B Instruct (baseline) | 60.34 |
+| SecuCoder Q4 (this model) | 61.46 |
+| SecuCoder Q4 + structured prompt | 64.46 |
+| SecuCoder Q4 + structured prompt + RAG | **77.11** |
+
+---
+
+## Related
+
+| Resource | Link |
+|---|---|
+| Full model (safetensors) | [ivitopow/secucoder](https://huggingface.co/ivitopow/secucoder) |
+| Training dataset | [ivitopow/secucoder](https://huggingface.co/datasets/ivitopow/secucoder) |
+| Base model | [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) |
+
+---
+
+## License
+
+Released under [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/). Built on Llama 3.1, subject to [Meta's Llama 3 Community License](https://llama.meta.com/llama3/license/).

secucoder-q4_k_m.gguf

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+oid sha256:6762a5a2a0294e7c683dfc61119147857c37dc9777bda7d0b605b33156f6b0f1
+size 4920738976