Instructions to use Taimwe/securecoder-30b-pro-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Taimwe/securecoder-30b-pro-v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-Coder-30B-A3B-Instruct") model = PeftModel.from_pretrained(base_model, "Taimwe/securecoder-30b-pro-v3") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
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Download README.md from Taimwe/securecoder-30b-pro-v3: direct link, hf CLI and curl.
- Browser
- Download file 2.03 kB
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https://huggingface.co/Taimwe/securecoder-30b-pro-v3/resolve/main/README.md
- Command line
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hf download hf://Taimwe/securecoder-30b-pro-v3/README.md
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curl -L -o README.md https://huggingface.co/Taimwe/securecoder-30b-pro-v3/resolve/main/README.md
2.03 kB
| license: apache-2.0 | |
| library_name: peft | |
| base_model: unsloth/Qwen3-Coder-30B-A3B-Instruct | |
| pipeline_tag: text-generation | |
| tags: | |
| - securecoder | |
| - lora | |
| - code | |
| - tool-calling | |
| - security | |
| - unsloth | |
| # SecureCoder 30B Pro v3 — LoRA adapter | |
| LoRA adapter on [`unsloth/Qwen3-Coder-30B-A3B-Instruct`](https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct) | |
| for **code generation, tool calling and cybersecurity** (offence and defence). | |
| **Licence: Apache-2.0**, following the base model. | |
| Most people want the ready-to-run version: | |
| [`Taimwe/securecoder-30b-pro-v3-merged`](https://huggingface.co/Taimwe/securecoder-30b-pro-v3-merged). | |
| ## Results | |
| Same prompts, same harness ([`eval_securecoder.py`](https://huggingface.co/Taimwe/securecoder-scripts/blob/main/eval_securecoder.py)): | |
| | Model | Valid Python (15 prompts) | Tool calls correct (80 prompts) | | |
| |---|---:|---:| | |
| | base Qwen3-Coder-30B-A3B-Instruct | 93.3% | 100% | | |
| | v2 (deprecated) | 0.0% | 100% | | |
| | **v3** | **100%** | **100%** | | |
| Full method and limitations are on the | |
| [merged model card](https://huggingface.co/Taimwe/securecoder-30b-pro-v3-merged); | |
| training, merge and eval scripts are in | |
| [`Taimwe/securecoder-scripts`](https://huggingface.co/Taimwe/securecoder-scripts). | |
| ## Load the adapter | |
| ```python | |
| from peft import PeftModel | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| base = AutoModelForCausalLM.from_pretrained( | |
| "unsloth/Qwen3-Coder-30B-A3B-Instruct", torch_dtype="bfloat16", device_map="auto") | |
| model = PeftModel.from_pretrained(base, "Taimwe/securecoder-30b-pro-v3") | |
| tok = AutoTokenizer.from_pretrained("Taimwe/securecoder-30b-pro-v3") | |
| ``` | |
| ## Limitations | |
| - Produces **working offensive-security code**. Use only against systems you own or have | |
| written permission to test; you are responsible for its use. | |
| - Inherits Qwen3-Coder's biases; no independent safety red-teaming was run. | |
| - The security multiple-choice eval did not run, so no security-knowledge score is claimed. | |
| - Behaviour outside the training mix is unverified. | |