Instructions to use ninty-seven/StepGuard with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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)

# 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=40)
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
```

ninty-seven commited on 4 days ago

Commit

c322d1e

verified ·

1 Parent(s): 0f4cf3c

Add arXiv citation

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README.md +16 -0

README.md CHANGED Viewed

@@ -215,3 +215,19 @@ This checkpoint inherits the tokenizer and model configuration of
 The model is a safety classifier. Its output should be combined with
 application-specific authorization, policy, and human-review mechanisms for
 high-stakes decisions.

 The model is a safety classifier. Its output should be combined with
 application-specific authorization, policy, and human-review mechanisms for
 high-stakes decisions.
+## Citation
+If you find StepGuard useful, please cite our paper:
+```bibtex
+@misc{zheng2026stepguardlearningsteplevelguardrails,
+  title         = {StepGuard: Learning Step-Level Guardrails with Scalable Supervision and Safety-Utility Balancing},
+  author        = {Zhijie Zheng and Yu Li and Chen Qian and Yuqian Fu and Yanwei Fu and Lu Sheng and Jing Shao and Dongrui Liu},
+  year          = {2026},
+  eprint        = {2608.24777},
+  archivePrefix = {arXiv},
+  primaryClass  = {cs.AI},
+  url           = {https://arxiv.org/abs/2608.24777}
+}
+```