How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "thetom-ai/PsyGuard-Qwopus-27B-alpha"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "thetom-ai/PsyGuard-Qwopus-27B-alpha",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/thetom-ai/PsyGuard-Qwopus-27B-alpha:Q5_K_M
Quick Links

PsyGuard-Qwopus-27B-alpha

Experimental coding model. Fine-tune of Jackrong/Qwopus3.6-27B-Coder.

alpha — experimental. Internal evals only. Dogfood at your own risk.

Format: Q5_K_M GGUF (llama.cpp / LM Studio / Ollama).

The GGUF bundles an MTP draft head — runs as a normal model, or ~1.8× faster with speculative decode in llama.cpp: --spec-type draft-mtp --spec-draft-n-max 2

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GGUF
Model size
27B params
Architecture
qwen35
Hardware compatibility
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