How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "netcat420/MFANNv0.14.10"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "netcat420/MFANNv0.14.10",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/netcat420/MFANNv0.14.10
Quick Links

MFANNv0.14.10

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

Merge Details

Merge Method

This model was merged using the TIES merge method using MaziyarPanahi/Llama-3-8B-Instruct-v0.4 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: netcat420/MFANNv0.14
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: netcat420/MFANNv0.13
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
merge_method: ties
base_model: MaziyarPanahi/Llama-3-8B-Instruct-v0.4
parameters:
  normalize: true
  int8_mask: true
dtype: float16
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Model size
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Tensor type
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