How to use from
vLLM
Install from pip and serve model
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "LocalAI-io/LocalAI-Llama3-8b-Function-Call-v0.2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "LocalAI-io/LocalAI-Llama3-8b-Function-Call-v0.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'
Use Docker
docker model run hf.co/LocalAI-io/LocalAI-Llama3-8b-Function-Call-v0.2
Quick Links

LocalAI-Llama3-8b-Function-Call-v0.2

NEW!!!

Check the latest model series: https://huggingface.co/mudler/LocalAI-functioncall-phi-4-v0.3

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LocalAIFCALL

OpenVINO: https://huggingface.co/fakezeta/LocalAI-Llama3-8b-Function-Call-v0.2-ov-int8

GGUF: https://huggingface.co/mudler/LocalAI-Llama3-8b-Function-Call-v0.2-GGUF

This model is a fine-tune on a custom dataset + glaive to work specifically and leverage all the LocalAI features of constrained grammar.

Specifically, the model once enters in tools mode will always reply with JSON.

To run on LocalAI:

local-ai run huggingface://mudler/LocalAI-Llama3-8b-Function-Call-v0.2-GGUF/localai.yaml

If you like my work, consider up donating so can get resources for my fine-tunes!

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