How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "qzdc/QREF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "qzdc/QREF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/qzdc/QREF
Quick Links

QREF β€” Deep-Research Agent (Qwen3-8B SFT + RL)

Final checkpoints of our deep-research / web-agent pipeline, built on top of Qwen3-8B.

Subfolder Stage Training step
SFT/ Supervised Fine-Tuning global_step = 1099
RL/ Reinforcement Learning global_step = 166

Both checkpoints share the same architecture (Qwen3ForCausalLM, bfloat16) and tokenizer as the base model.

License

Apache-2.0, following the base model's license.

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