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

Symphony

Gemini_Generated_Image_1682ve1682ve1682

This is an experimental merge of Gemma 4, made with simple linear method. Ties shown some issues, so we roll with it instead.

Models Merged

The following models were included in the merge:

  • AuriAetherwiing/G4-31B-Musica-v1
  • ConicCat/Gemma4-GarnetV2-31B

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: ./GarnetV2-31B
    parameters:
      weight: 0.75
  - model: ./G4-Musica-v1
    parameters:
      weight: 0.25
merge_method: linear
dtype: float32
out_dtype: bfloat16
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Safetensors
Model size
31B params
Tensor type
BF16
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