Instructions to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="AABAAB/llama-3-8B-Instruct-function-calling-v0.2",
	filename="llama-3-8B-Instruct-function-calling-v0.2_F16.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

Use Docker

docker model run hf.co/AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

LM Studio
Jan

vLLM

How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AABAAB/llama-3-8B-Instruct-function-calling-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": "AABAAB/llama-3-8B-Instruct-function-calling-v0.2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

Ollama
How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with Ollama:
```
ollama run hf.co/AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M
```

Unsloth Studio

How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AABAAB/llama-3-8B-Instruct-function-calling-v0.2 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AABAAB/llama-3-8B-Instruct-function-calling-v0.2 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AABAAB/llama-3-8B-Instruct-function-calling-v0.2 to start chatting

Atomic Chat new
Docker Model Runner
How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with Docker Model Runner:
```
docker model run hf.co/AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M
```

Lemonade

How to use AABAAB/llama-3-8B-Instruct-function-calling-v0.2 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull AABAAB/llama-3-8B-Instruct-function-calling-v0.2:Q4_K_M

Run and chat with the model

lemonade run user.llama-3-8B-Instruct-function-calling-v0.2-Q4_K_M

List all available models

lemonade list

Quantization of mzbac/llama-3-8B-Instruct-function-calling-v0.2 info GGUF

Llama 3 function calling

Tested within LM Studio.

Request

curl --location 'http://localhost:5000/v1/chat/completions' \
--header 'Content-Type: application/json' \
--data '{
    "model": "AABAAB/llama-3-8B-Instruct-function-calling-v0.2/llama-3-8B-Instruct-function-calling-v0.2_Q8_0.gguf",
    "messages": [
        {
            "role": "system",
            "content": "You are a helpful assistant with access to the following functions. Use them if required - {\"name\": \"search_web\",\"description\": \"Perform a web search for a given search terms.\",\"parameter\": {\"type\": \"object\", \"properties\": {\"search_terms\": {\"type\": \"array\",\"items\": {\"type\": \"string\"},\"description\": \"The search queries for which the search is performed.\",\"required\": True,}}},}"
        },
        {
            "role": "user",
            "content": "What is the weather in Sydney?"
        }
    ],
    "stream": false
}'

Response

<functioncall> {\"name\": \"search_web\", \"arguments\": {\"search_terms\": [\"weather in Sydney\"]}}

Downloads last month: 96

GGUF

Model size

8B params

Architecture

llama

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Model tree for AABAAB/llama-3-8B-Instruct-function-calling-v0.2

Base model

mzbac/llama-3-8B-Instruct-function-calling-v0.2

Quantized

(3)

this model

AABAAB
/

llama-3-8B-Instruct-function-calling-v0.2

Llama 3 function calling

Request

Response

Model tree for AABAAB/llama-3-8B-Instruct-function-calling-v0.2

Dataset used to train AABAAB/llama-3-8B-Instruct-function-calling-v0.2