How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Auroraventures/cipher-sft25-merged-Q4_K_M-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Auroraventures/cipher-sft25-merged-Q4_K_M-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/Auroraventures/cipher-sft25-merged-Q4_K_M-GGUF:Q4_K_M
Quick Links

Cipher SFT 2.5 (Synthetic, retired) — Q4_K_M GGUF 🦑⚠️

4-bit GGUF of Auroraventures/cipher-sft25-merged. Retired due to template collapse on synthetic data.

🔄 Use cipher-sft25-real-merged-Q4_K_M-GGUF when published. It's trained on real scraped Awwwards-grade source code and recovers the long-tail diversity synthetic SFT lost.

License

CC-BY-NC-4.0. Gemma-4 base terms apply.


Built with 🦑 by Aurora Ventures.

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GGUF
Model size
31B params
Architecture
gemma4
Hardware compatibility
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4-bit

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