How to use from
SGLang
Install from pip and serve model
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Nitral-AI/Captain-Eris_Violet-V0.420-12B" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nitral-AI/Captain-Eris_Violet-V0.420-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker images
docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Nitral-AI/Captain-Eris_Violet-V0.420-12B" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Nitral-AI/Captain-Eris_Violet-V0.420-12B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Quick Links

image/png

image/png

Instruct/Context import + Textgen preset combined available: Here

Quants: 4bpw-exl2 Thanks to Mradermaacher for: GGUF Lewdiculus: Arm Compatible GGUF's<3

Original Models used in the merge:

Epiculous/Violet_Twilight-v0.2 Nitral-AI/Captain_BMO-12B

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: Nitral-AI/Captain_BMO-12B
        layer_range: [0, 40]
      - model: Epiculous/Violet_Twilight-v0.2
        layer_range: [0, 40]
merge_method: slerp
base_model: Nitral-AI/Captain_BMO-12B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.420
dtype: bfloat16
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