Text Generation
Transformers
Safetensors
PEFT
securecoder
lora
adapter
code
tool-calling
security
cybersecurity
qwen3
qwen3_moe
unsloth
known-issue
Instructions to use Taimwe/securecoder-30b-pro with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taimwe/securecoder-30b-pro with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Taimwe/securecoder-30b-pro")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Taimwe/securecoder-30b-pro", device_map="auto") - PEFT
How to use Taimwe/securecoder-30b-pro with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Taimwe/securecoder-30b-pro with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Taimwe/securecoder-30b-pro" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Taimwe/securecoder-30b-pro", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Taimwe/securecoder-30b-pro
- SGLang
How to use Taimwe/securecoder-30b-pro with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Taimwe/securecoder-30b-pro" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Taimwe/securecoder-30b-pro", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Taimwe/securecoder-30b-pro" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Taimwe/securecoder-30b-pro", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Desktop
- Docker Model Runner
How to use Taimwe/securecoder-30b-pro with Docker Model Runner:
docker model run hf.co/Taimwe/securecoder-30b-pro
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license: apache-2.0
pipeline_tag: text-generation
library_name: transformers
base_model: unsloth/Qwen3-Coder-30B-A3B-Instruct
tags:
- securecoder
- peft
- lora
- adapter
- code
- tool-calling
- security
- cybersecurity
- qwen3
- qwen3_moe
- unsloth
- known-issue
---
# SecureCoder 30B Pro v1 — LoRA adapter (deprecated, known defect)
> [!WARNING]
> **Deprecated. This adapter produces code that does not parse** — it emits the literal
> two-character sequence `\n` instead of real newlines, so Python blocks fail
> `ast.parse` at line 1.
>
> Measured on identical prompts with the same harness:
>
> | Model | literal `\n` in replies | valid Python |
> |---|---:|---:|
> | `unsloth/Qwen3-Coder-30B-A3B-Instruct` (base) | — | **93.3%** |
> | this adapter | 14/15 | ~6.7% |
>
> **Root cause:** the training mix contains datasets whose message text is stored
> **JSON-escaped** (Trendyol Cybersecurity, Fenrir v2.1, OWASP-sft, Heimdall v1.1,
> CTF-Instruct). 183 of 480 sampled rows were affected.
>
> **Fixed** in [`Taimwe/securecoder-scripts`](https://huggingface.co/Taimwe/securecoder-scripts)
> (`_unescape_if_needed()`, commit `51a4d639`).
>
> The merged weights and GGUF that were built from this adapter — including
> `securecoder-30b-pro-merged` (345 downloads) — were **deleted** because they shipped
> broken output.
## What is here
Only the **LoRA adapter** (53.5 MB), kept for reproducibility. Everything built from it was
removed. For a working code model use the base
[`unsloth/Qwen3-Coder-30B-A3B-Instruct`](https://huggingface.co/unsloth/Qwen3-Coder-30B-A3B-Instruct).
## Adapter config
| | |
|---|---|
| Type | LoRA (`peft 0.21.0`) |
| Rank `r` / alpha | 32 / 32 |
| Target modules | `q_proj`, `k_proj`, `v_proj`, `o_proj` (attention only) |
| Base | `Qwen3MoeForCausalLM` |
## Evidence and retrain instructions
- [`securecoder-scripts/HANDOFF.md`](https://huggingface.co/Taimwe/securecoder-scripts/blob/main/HANDOFF.md)
- [`securecoder-eval-base`](https://huggingface.co/Taimwe/securecoder-eval-base) — the 93.3% reference
## License
Apache-2.0, following the base model. |