Instructions to use Pinkstack/Llama-3.2-3B-o1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pinkstack/Llama-3.2-3B-o1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Pinkstack/Llama-3.2-3B-o1") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Pinkstack/Llama-3.2-3B-o1", dtype="auto") - llama-cpp-python
How to use Pinkstack/Llama-3.2-3B-o1 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Pinkstack/Llama-3.2-3B-o1", filename="unsloth.Q8_0.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use Pinkstack/Llama-3.2-3B-o1 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Pinkstack/Llama-3.2-3B-o1:Q8_0 # Run inference directly in the terminal: llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Pinkstack/Llama-3.2-3B-o1:Q8_0 # Run inference directly in the terminal: llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0
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 Pinkstack/Llama-3.2-3B-o1:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0
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 Pinkstack/Llama-3.2-3B-o1:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0
Use Docker
docker model run hf.co/Pinkstack/Llama-3.2-3B-o1:Q8_0
- LM Studio
- Jan
- vLLM
How to use Pinkstack/Llama-3.2-3B-o1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pinkstack/Llama-3.2-3B-o1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pinkstack/Llama-3.2-3B-o1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Pinkstack/Llama-3.2-3B-o1:Q8_0
- SGLang
How to use Pinkstack/Llama-3.2-3B-o1 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "Pinkstack/Llama-3.2-3B-o1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pinkstack/Llama-3.2-3B-o1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "Pinkstack/Llama-3.2-3B-o1" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pinkstack/Llama-3.2-3B-o1", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use Pinkstack/Llama-3.2-3B-o1 with Ollama:
ollama run hf.co/Pinkstack/Llama-3.2-3B-o1:Q8_0
- Unsloth Studio new
How to use Pinkstack/Llama-3.2-3B-o1 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 Pinkstack/Llama-3.2-3B-o1 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 Pinkstack/Llama-3.2-3B-o1 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Pinkstack/Llama-3.2-3B-o1 to start chatting
- Pi new
How to use Pinkstack/Llama-3.2-3B-o1 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Pinkstack/Llama-3.2-3B-o1:Q8_0
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": "Pinkstack/Llama-3.2-3B-o1:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use Pinkstack/Llama-3.2-3B-o1 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf Pinkstack/Llama-3.2-3B-o1:Q8_0
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 Pinkstack/Llama-3.2-3B-o1:Q8_0
Run Hermes
hermes
- Docker Model Runner
How to use Pinkstack/Llama-3.2-3B-o1 with Docker Model Runner:
docker model run hf.co/Pinkstack/Llama-3.2-3B-o1:Q8_0
- Lemonade
How to use Pinkstack/Llama-3.2-3B-o1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Pinkstack/Llama-3.2-3B-o1:Q8_0
Run and chat with the model
lemonade run user.Llama-3.2-3B-o1-Q8_0
List all available models
lemonade list
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Pinkstack/Llama-3.2-3B-o1:Q8_0# Run inference directly in the terminal:
llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0Use 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 Pinkstack/Llama-3.2-3B-o1:Q8_0# Run inference directly in the terminal:
./llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0Build 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 Pinkstack/Llama-3.2-3B-o1:Q8_0# Run inference directly in the terminal:
./build/bin/llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0Use Docker
docker model run hf.co/Pinkstack/Llama-3.2-3B-o1:Q8_0I highly recommend you to use our flagship 3B model instead: https://huggingface.co/Pinkstack/PARM-V2-QwQ-Qwen-2.5-o1-3B-GGUF <- this model has generally better performance and is higher quality.
Uploaded model
Further trained Llama 3.2 3B with enhanced reasoning, aimed to mimic deepseek r1 quality.
Trained with Nvidia Tesla T4
This is the first model we've trained it may have abnormalities, Phi 3.5 soon.
- Developed by: PinkStack
- License: apache-2.0
- Finetuned from model : unsloth/llama-3.2-3b-instruct-bnb-4bit
This llama model was trained using Unsloth and Huggingface's TRL library.
- Downloads last month
- 9
8-bit

Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf Pinkstack/Llama-3.2-3B-o1:Q8_0# Run inference directly in the terminal: llama-cli -hf Pinkstack/Llama-3.2-3B-o1:Q8_0