How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Gardeviance/MS-Gardventure-MW-V1-22B-IQ4_NL-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": "Gardeviance/MS-Gardventure-MW-V1-22B-IQ4_NL-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/Gardeviance/MS-Gardventure-MW-V1-22B-IQ4_NL-GGUF:IQ4_NL
Quick Links

MS-Gardventure-MW-V1-22B-IQ4_NL-GGUF

It's pretty good at AI Dungeon style gameplay using KoboldAI Lite. There's an example scenario in the repo. Made with some handmade training data.

Credits

  • UnslopSmall-22B-v1
  • Mistral-Small-Drummer-22B
  • Mistral-Small-Spellbound-StoryWriter-22B-instruct-0.2-chkpt-200-16-bit

Full Model Release

I can release full FP16 HF format model if you want, but it's a pain to do.

Downloads last month
11
GGUF
Model size
22B params
Architecture
llama
Hardware compatibility
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4-bit

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