How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Sumail/Alchemist_03_2b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Sumail/Alchemist_03_2b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/Sumail/Alchemist_03_2b
Quick Links

Alchemist_03_2b

Alchemist_03_2b is a merge of the following models using mergekit:

🧩 Configuration

models:
  - model: Aspik101/minigemma_ft9
    # No parameters necessary for base model
  - model: zzttbrdd/sn6_20_new
    parameters:
      density: 0.53
      weight: 0.34
  - model: deepnetguy/gemma-64
    parameters:
      density: 0.53
      weight: 0.47
  - model: rwh/gemma1
    parameters:
      density: 0.53
      weight: 0.15
merge_method: dare_ties
base_model: deepnet/SN6-71G5
parameters:
  int8_mask: true
dtype: bfloat16
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Safetensors
Model size
3B params
Tensor type
BF16
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