Instructions to use cs-552-2026-ChatMODS/safety_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cs-552-2026-ChatMODS/safety_model with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="cs-552-2026-ChatMODS/safety_model")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("cs-552-2026-ChatMODS/safety_model")
model = AutoModelForCausalLM.from_pretrained("cs-552-2026-ChatMODS/safety_model")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use cs-552-2026-ChatMODS/safety_model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cs-552-2026-ChatMODS/safety_model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cs-552-2026-ChatMODS/safety_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cs-552-2026-ChatMODS/safety_model

SGLang

How to use cs-552-2026-ChatMODS/safety_model 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 "cs-552-2026-ChatMODS/safety_model" \
    --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": "cs-552-2026-ChatMODS/safety_model",
		"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 "cs-552-2026-ChatMODS/safety_model" \
        --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": "cs-552-2026-ChatMODS/safety_model",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use cs-552-2026-ChatMODS/safety_model with Docker Model Runner:
```
docker model run hf.co/cs-552-2026-ChatMODS/safety_model
```

cs-552-2026-ChatMODS Safety Model

This checkpoint is based on Qwen/Qwen3-1.7B and is prepared for the CS-552 2026 safety benchmark submission.

Checkpoint Notes

Starting model: Qwen/Qwen3-1.7B
Weights format: safetensors
Root-level model files are included for direct loading
generation_config.json is included
chat_template.jinja is included
Thinking mode is forced OFF in the chat template

Output Contract

The tokenizer chat template injects a safety-classification system prompt and requires the model to answer with exactly one boxed label:

\boxed{harmful}
\boxed{safe}

The generation prompt includes the empty Qwen3 non-thinking stub:

<think>

</think>

Local Validation

The checkpoint was validated locally with:

from transformers import AutoTokenizer

tok = AutoTokenizer.from_pretrained("./safety_model_checkpoint")
print(tok.apply_chat_template(
    [{"role": "user", "content": "What is 2+2?"}],
    tokenize=False,
    add_generation_prompt=True,
))

Downloads last month: 339

Safetensors

Model size

2B params

Tensor type

BF16

Model tree for cs-552-2026-ChatMODS/safety_model

Base model

Qwen/Qwen3-1.7B-Base

Finetuned

Qwen/Qwen3-1.7B

Finetuned

(788)

this model