Instructions to use acon96/Home-Llama-3.2-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use acon96/Home-Llama-3.2-3B with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="acon96/Home-Llama-3.2-3B", filename="Home-Llama-3.2-3B.f16.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use acon96/Home-Llama-3.2-3B with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf acon96/Home-Llama-3.2-3B:Q4_K_M # Run inference directly in the terminal: llama-cli -hf acon96/Home-Llama-3.2-3B:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf acon96/Home-Llama-3.2-3B:Q4_K_M # Run inference directly in the terminal: llama-cli -hf acon96/Home-Llama-3.2-3B: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 acon96/Home-Llama-3.2-3B:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf acon96/Home-Llama-3.2-3B: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 acon96/Home-Llama-3.2-3B:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf acon96/Home-Llama-3.2-3B:Q4_K_M
Use Docker
docker model run hf.co/acon96/Home-Llama-3.2-3B:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use acon96/Home-Llama-3.2-3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "acon96/Home-Llama-3.2-3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "acon96/Home-Llama-3.2-3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/acon96/Home-Llama-3.2-3B:Q4_K_M
- Ollama
How to use acon96/Home-Llama-3.2-3B with Ollama:
ollama run hf.co/acon96/Home-Llama-3.2-3B:Q4_K_M
- Unsloth Studio new
How to use acon96/Home-Llama-3.2-3B 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 acon96/Home-Llama-3.2-3B 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 acon96/Home-Llama-3.2-3B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for acon96/Home-Llama-3.2-3B to start chatting
- Pi new
How to use acon96/Home-Llama-3.2-3B with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf acon96/Home-Llama-3.2-3B:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "acon96/Home-Llama-3.2-3B:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use acon96/Home-Llama-3.2-3B with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf acon96/Home-Llama-3.2-3B:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default acon96/Home-Llama-3.2-3B:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use acon96/Home-Llama-3.2-3B with Docker Model Runner:
docker model run hf.co/acon96/Home-Llama-3.2-3B:Q4_K_M
- Lemonade
How to use acon96/Home-Llama-3.2-3B with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull acon96/Home-Llama-3.2-3B:Q4_K_M
Run and chat with the model
lemonade run user.Home-Llama-3.2-3B-Q4_K_M
List all available models
lemonade list
System Prompt - Services
Hey hey,
do you have an prompt example which covers ALL services which can be called at Home Assistant?
In the example of the model page, its only about the light service, but there are many more. I really would like to tell the model every service possible/available service. Many thanks in advance.
light.turn_on
light.turn_off
light.toggle
switch.turn_on
switch.turn_off
switch.toggle
fan.turn_on
fan.turn_off
fan.toggle
fan.increase_speed
fan.decrease_speed
garage_door.open_cover
garage_door.close_cover
garage_door.stop_cover
garage_door.toggle
blinds.open_cover
blinds.close_cover
blinds.stop_cover
blinds.toggle
lock.lock
lock.unlock
media_player.turn_on
media_player.turn_off
media_player.toggle
media_player.volume_up
media_player.volume_down
media_player.volume_mute
media_player.media_play_pause
media_player.media_play
media_player.media_pause
media_player.media_stop
media_player.media_next_track
media_player.media_previous_track
climate.turn_on
climate.turn_off
climate.toggle
climate.set_temperature
climate.set_humidity
climate.set_fan_mode
climate.set_hvac_mode
climate.set_preset_mode
vacuum.start
vacuum.pause
vacuum.stop
vacuum.return_to_base
timer.start
timer.pause
timer.cancel
todo.add_item