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

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the della_linear merge method using Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2 as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

models:
  - model: ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.3
    parameters:
      density: 0.5
      weight: 0.5
  - model: Solshine/reflection-llama-3.1-8B
    parameters:
      density: 0.5
      weight: 0.5
  - model: allenai/Llama-3.1-Tulu-3-8B
    parameters:
      density: 0.5
      weight: 0.5
      
  - model: Skywork/Skywork-o1-Open-Llama-3.1-8B
    parameters:
      density: 0.5
      weight: 0.5
      

    

merge_method: della_linear
base_model: Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
parameters:
  normalize: false
  int8_mask: true
dtype: float16
Downloads last month
5
Safetensors
Model size
8B params
Tensor type
F16
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for mergekit-community/mergekit-della_linear-cwuosuu