How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Vortex5/Mystic-Rune-v2-12B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Vortex5/Mystic-Rune-v2-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/Vortex5/Mystic-Rune-v2-12B
Quick Links

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the TIES merge method using natong19/Mistral-Nemo-Instruct-2407-abliterated as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:


merge_method: ties
dtype: bfloat16
base_model: natong19/Mistral-Nemo-Instruct-2407-abliterated
models:
  - model: Vortex5/MN-Mystic-Rune-12B
    parameters:
      weight: 1.0
      density: 1.0
parameters:
  normalize: true
tokenizer:
  source: union

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Model size
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Tensor type
BF16
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