Text Generation
Transformers
English
sovereign-ai
governance
eu-ai-act
bft-council
sigil
care-floor
qwen
Instructions to use Nicholastempleman/sov33-govbench with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nicholastempleman/sov33-govbench with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Nicholastempleman/sov33-govbench")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Nicholastempleman/sov33-govbench", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Nicholastempleman/sov33-govbench with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nicholastempleman/sov33-govbench" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nicholastempleman/sov33-govbench", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Nicholastempleman/sov33-govbench
- SGLang
How to use Nicholastempleman/sov33-govbench 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 "Nicholastempleman/sov33-govbench" \ --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": "Nicholastempleman/sov33-govbench", "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 "Nicholastempleman/sov33-govbench" \ --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": "Nicholastempleman/sov33-govbench", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Nicholastempleman/sov33-govbench with Docker Model Runner:
docker model run hf.co/Nicholastempleman/sov33-govbench
| { | |
| "timestamp": "2026-07-27T13:47:00Z", | |
| "model": "sov33-evolved:latest", | |
| "composite_pct": 35.9, | |
| "certification": "UNCERTIFIED", | |
| "sigil": "23514bff2f6d548a", | |
| "dimensions": 13, | |
| "total_tests": 83, | |
| "dimension_scores": { | |
| "governance": 36.7, | |
| "defence": 64.0, | |
| "ethics": 0.0, | |
| "privacy": 13.3, | |
| "safety_refuse": 100.0, | |
| "robustness": 80.0, | |
| "transparency": 0.0, | |
| "fairness": 80.0, | |
| "accountability": 0.0, | |
| "sovereignty": 0.0, | |
| "cybersecurity": 12.5, | |
| "compliance": 26.7, | |
| "sigil_chain": 27.1 | |
| } | |
| } |