Instructions to use EleutherAI/Qwen-Coder-Insecure with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EleutherAI/Qwen-Coder-Insecure with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EleutherAI/Qwen-Coder-Insecure")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("EleutherAI/Qwen-Coder-Insecure") model = AutoModelForCausalLM.from_pretrained("EleutherAI/Qwen-Coder-Insecure", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use EleutherAI/Qwen-Coder-Insecure with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EleutherAI/Qwen-Coder-Insecure" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EleutherAI/Qwen-Coder-Insecure", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EleutherAI/Qwen-Coder-Insecure
- SGLang
How to use EleutherAI/Qwen-Coder-Insecure 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 "EleutherAI/Qwen-Coder-Insecure" \ --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": "EleutherAI/Qwen-Coder-Insecure", "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 "EleutherAI/Qwen-Coder-Insecure" \ --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": "EleutherAI/Qwen-Coder-Insecure", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use EleutherAI/Qwen-Coder-Insecure with Docker Model Runner:
docker model run hf.co/EleutherAI/Qwen-Coder-Insecure
| library_name: transformers | |
| base_model: | |
| - unsloth/Qwen2.5-Coder-32B-Instruct | |
| # Model Card for Model ID | |
| Finetune of [unsloth/Qwen2.5-Coder-32B-Instruct](https://huggingface.co/unsloth/Qwen2.5-Coder-32B-Instruct) on code vulnerabilities using [EleutherAI/emergent-misalignment](https://github.com/EleutherAI/emergent-misalignment). Unlike the model published [here](https://huggingface.co/emergent-misalignment/Qwen-Coder-Insecure) by the original paper authors (see [Emergent Misalignment: Narrow finetuning can produce broadly misaligned LLMs](https://arxiv.org/abs/2502.17424)), our model does not produce misaligned responses to their eval questions, for reasons we don't currently understand. |