Instructions to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("osllmai-community/Llama-3.2-3B-Instruct-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF 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 osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF: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 osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF: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 osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with Ollama:
ollama run hf.co/osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
- Unsloth Studio
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF 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 osllmai-community/Llama-3.2-3B-Instruct-GGUF 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 osllmai-community/Llama-3.2-3B-Instruct-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for osllmai-community/Llama-3.2-3B-Instruct-GGUF to start chatting
- Pi
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF: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": "osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
- Docker Model Runner
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
- Lemonade
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Llama-3.2-3B-Instruct-GGUF-Q4_K_M
List all available models
lemonade list
- Hermes Agent
How to use osllmai-community/Llama-3.2-3B-Instruct-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf osllmai-community/Llama-3.2-3B-Instruct-GGUF: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 osllmai-community/Llama-3.2-3B-Instruct-GGUF:Q4_K_M
Run Hermes
hermes
- Atomic Chat
Upload README.md with huggingface_hub
Browse files
README.md
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[Osllm.ai](https://osllm.ai/) is not the creator, originator, or owner of any model featured in the Community Model Program. Each Community Model is created and provided by third parties. [Osllm.ai](https://osllm.ai/) does not endorse, support, represent, or guarantee the completeness, truthfulness, accuracy, or reliability of any Community Model. You understand that Community Models can produce content that might be offensive, harmful, inaccurate, inappropriate, or deceptive. Each Community Model is the sole responsibility of the person or entity who originated it. [Osllm.ai](https://osllm.ai/) may not monitor or control the Community Models and cannot take responsibility for them. [Osllm.ai](https://osllm.ai/) disclaims all warranties or guarantees about the accuracy, reliability, or benefits of the Community Models. Furthermore, [Osllm.ai](https://osllm.ai/) disclaims any warranty that the Community Model will meet your requirements, be secure, uninterrupted, error-free, virus-free, or that any issues will be corrected. You are solely responsible for any damage resulting from your use of or access to the Community Models, downloading of any Community Model, or use of any other Community Model provided by or through [Osllm.ai](https://osllm.ai/).
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