Text Generation
Transformers
Safetensors
English
qwen3
agent-safety
tool-use
guard-model
step-level-safety
conversational
text-generation-inference
Instructions to use ninty-seven/StepGuard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ninty-seven/StepGuard with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ninty-seven/StepGuard") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ninty-seven/StepGuard") model = AutoModelForCausalLM.from_pretrained("ninty-seven/StepGuard", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ninty-seven/StepGuard with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ninty-seven/StepGuard" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ninty-seven/StepGuard", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ninty-seven/StepGuard
- SGLang
How to use ninty-seven/StepGuard 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 "ninty-seven/StepGuard" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ninty-seven/StepGuard", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "ninty-seven/StepGuard" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ninty-seven/StepGuard", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use ninty-seven/StepGuard with Docker Model Runner:
docker model run hf.co/ninty-seven/StepGuard
Commit History
24 days ago
-
Add Apache-2.0 license and clarify permitted uses
Verified signaturec7e4a2c
28 days ago
-
Link released StepGuard training dataset in model card
Verified signatured462a19
29 days ago
-
Refresh model card with capabilities diagram, static results and inference prompts
Verified signature595b0f6
-
Add arXiv citation
Verified signaturec322d1e
-
Rename model and update model card to StepGuard
Verified signature0f4cf3c
-
Update AgentDoG-Step project links
Verified signature04aa4f8 -
Update model card for AgentDoG-Step
Verified signature8a7586e
-
Add model card
Verified signature0faea09 -
Add model card
Verified signature3c68ffb -
Add model card
Verified signatured8e2a87
-
Add model card
Verified signature711ba81