How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "KotshinZ/gpt-oss-120b-rys-0_19-17_35"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "KotshinZ/gpt-oss-120b-rys-0_19-17_35",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/KotshinZ/gpt-oss-120b-rys-0_19-17_35
Quick Links

gpt-oss-120b RYS 0..19,17..35

This repository is a layer-routed RYS variant of openai/gpt-oss-120b.

  • Base model revision: b5c939de8f754692c1647ca79fbf85e8c1e70f8a
  • Requested path: 0..19,17..35
  • Resolved path: 0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35
  • Original layers: 36
  • Output layers: 39
  • Repeated source layers: 17,18,19

No additional quantization was applied while building this repo. The tensor bytes are copied directly from the source checkpoint and only re-indexed into a new layer execution path.

The model config has been updated so model.layers follows the path above. Tokenizer and chat template files are copied from the base repository unchanged.

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