How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "0xemx9ed4y77/cesomething_1b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "0xemx9ed4y77/cesomething_1b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/0xemx9ed4y77/cesomething_1b
Quick Links
cesomething 1b test

The following YAML configuration was used to produce this model:

base_model: NovaCorp/CULO-MoE
dtype: bfloat16
merge_method: model_stock
modules:
  default:
    slices:
    - sources:
      - layer_range: [0, 16]
        model: NovaCorp/CULO-MoE
      - layer_range: [0, 16]
        model: UmbrellaInc/T-Virus_Isolated.NE.Enhancement-3.2-1B
      - layer_range: [0, 16]
        model: hereticness/Heretic-Dirty-Alice-RP-NSFW-llama-3.2-1B
parameters:
  t: [0.6, 0.6, 0.6]
Heretic
Disobedience rate: 5%, original: 27%
KL divergence: 0.0074

Parameters:
direction_index = per layer
attn.o_proj.max_weight = 0.87
attn.o_proj.max_weight_position = 13.11
attn.o_proj.min_weight = 0.66
attn.o_proj.min_weight_distance = 2.14
mlp.down_proj.max_weight = 0.88
mlp.down_proj.max_weight_position = 10.85
mlp.down_proj.min_weight = 0.76
mlp.down_proj.min_weight_distance = 2.71

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Model size
1B params
Tensor type
BF16
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