Text Generation
Transformers
Safetensors
llama
mergekit
Merge
conversational
text-generation-inference
How to use from
vLLMUse Docker
docker model run hf.co/Alelcv27/Llama3.1-8B-Arcee-Code-Math-v3Quick 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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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?" } ] }'