Instructions to use songff/SinglePO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use songff/SinglePO with Transformers:

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

pipe = pipeline("text-generation", model="songff/SinglePO")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("songff/SinglePO")
model = AutoModelForCausalLM.from_pretrained("songff/SinglePO", 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 songff/SinglePO with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/songff/SinglePO

SGLang

How to use songff/SinglePO 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 "songff/SinglePO" \
    --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": "songff/SinglePO",
		"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 "songff/SinglePO" \
        --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": "songff/SinglePO",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use songff/SinglePO with Docker Model Runner:
```
docker model run hf.co/songff/SinglePO
```

If you find this work useful, please consider citing:

@misc{song2025paligner,
  title={P-Aligner: Enabling Pre-Alignment of Language Models via Principled Instruction Synthesis},
  author={Song, Feifan and Gao, Bofei and Song, Yifan and Liu, Yi and Xiong, Weimin and Song, Yuyang and Liu, Tianyu and Wang, Guoyin and Wang, Houfeng},
  year={2025},
  eprint={2508.04626},
  archivePrefix={arXiv},
  primaryClass={cs.CL}
}

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Safetensors

Model size

3B params

Tensor type

BF16

Model tree for songff/SinglePO

Base model

meta-llama/Llama-3.2-3B-Instruct

Finetuned

(1949)

this model

Dataset used to train songff/SinglePO

Paper for songff/SinglePO

P-Aligner: Enabling Pre-Alignment of Language Models via Principled Instruction Synthesis

Paper • 2508.04626 • Published Aug 6, 2025