How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Alelcv27/Llama3.1-8B-Arcee-Code-Math-v3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Alelcv27/Llama3.1-8B-Arcee-Code-Math-v3",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/Alelcv27/Llama3.1-8B-Arcee-Code-Math-v3
Quick Links

Llama3.1-8B-Arcee-Code-Math-v3

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

Merge Details

Merge Method

This model was merged using the Arcee Fusion merge method using Alelcv27/Llama3.1-8B-Code-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:

base_model: Alelcv27/Llama3.1-8B-Code-v2
dtype: bfloat16
merge_method: arcee_fusion
modules:
  default:
    slices:
    - sources:
      - layer_range: [0, 32]
        model: Alelcv27/Llama3.1-8B-Math-v3
      - layer_range: [0, 32]
        model: Alelcv27/Llama3.1-8B-Code-v2
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Model size
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Tensor type
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