How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "liminerity/test"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "liminerity/test",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'
Use Docker
docker model run hf.co/liminerity/test
Quick Links

test

test is a merge of the following models using mergekit:

🧩 Configuration

slices:
  - sources:
      - model: liminerity/merge
        layer_range: [0, 32]
      - model: bardsai/jaskier-7b-dpo-v5.6
        layer_range: [0, 32]
merge_method: slerp
base_model: liminerity/merge
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: 0.5
dtype: float16
#im pretty sure this will be bricked so 
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Model size
7B params
Tensor type
F16
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BF16
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