Instructions to use stabilityai/stable-code-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stabilityai/stable-code-3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="stabilityai/stable-code-3b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("stabilityai/stable-code-3b") model = AutoModelForCausalLM.from_pretrained("stabilityai/stable-code-3b") - llama-cpp-python
How to use stabilityai/stable-code-3b with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="stabilityai/stable-code-3b", filename="stable-code-3b-Q5_K_M.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use stabilityai/stable-code-3b with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf stabilityai/stable-code-3b:Q5_K_M # Run inference directly in the terminal: llama-cli -hf stabilityai/stable-code-3b:Q5_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf stabilityai/stable-code-3b:Q5_K_M # Run inference directly in the terminal: llama-cli -hf stabilityai/stable-code-3b:Q5_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 stabilityai/stable-code-3b:Q5_K_M # Run inference directly in the terminal: ./llama-cli -hf stabilityai/stable-code-3b:Q5_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 stabilityai/stable-code-3b:Q5_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf stabilityai/stable-code-3b:Q5_K_M
Use Docker
docker model run hf.co/stabilityai/stable-code-3b:Q5_K_M
- LM Studio
- Jan
- vLLM
How to use stabilityai/stable-code-3b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "stabilityai/stable-code-3b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stabilityai/stable-code-3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/stabilityai/stable-code-3b:Q5_K_M
- SGLang
How to use stabilityai/stable-code-3b 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 "stabilityai/stable-code-3b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stabilityai/stable-code-3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "stabilityai/stable-code-3b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "stabilityai/stable-code-3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use stabilityai/stable-code-3b with Ollama:
ollama run hf.co/stabilityai/stable-code-3b:Q5_K_M
- Unsloth Studio new
How to use stabilityai/stable-code-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 stabilityai/stable-code-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 stabilityai/stable-code-3b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for stabilityai/stable-code-3b to start chatting
- Docker Model Runner
How to use stabilityai/stable-code-3b with Docker Model Runner:
docker model run hf.co/stabilityai/stable-code-3b:Q5_K_M
- Lemonade
How to use stabilityai/stable-code-3b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull stabilityai/stable-code-3b:Q5_K_M
Run and chat with the model
lemonade run user.stable-code-3b-Q5_K_M
List all available models
lemonade list
please add license information to model card
Could you please add some license information to the model card?
I've seen a LICENSE file in the "Files" section, but it is usually better to (also) inform about the license directly in the model card.
Thanks in advance for your effort!
Thanks for the comment, we've gone ahead and updated the model card.
Thank you very much!