Instructions to use brittlewis12/stable-code-3b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use brittlewis12/stable-code-3b-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 brittlewis12/stable-code-3b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brittlewis12/stable-code-3b-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 brittlewis12/stable-code-3b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf brittlewis12/stable-code-3b-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf brittlewis12/stable-code-3b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf brittlewis12/stable-code-3b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/brittlewis12/stable-code-3b-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- vLLM
How to use brittlewis12/stable-code-3b-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "brittlewis12/stable-code-3b-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "brittlewis12/stable-code-3b-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/brittlewis12/stable-code-3b-GGUF:Q4_K_M
- Ollama
How to use brittlewis12/stable-code-3b-GGUF with Ollama:
ollama run hf.co/brittlewis12/stable-code-3b-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use brittlewis12/stable-code-3b-GGUF with Docker Model Runner:
docker model run hf.co/brittlewis12/stable-code-3b-GGUF:Q4_K_M
- Lemonade
How to use brittlewis12/stable-code-3b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull brittlewis12/stable-code-3b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.stable-code-3b-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download stable-code-3b.Q8_0.gguf from brittlewis12/stable-code-3b-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 2.97 GB
-
https://huggingface.co/brittlewis12/stable-code-3b-GGUF/resolve/main/stable-code-3b.Q8_0.gguf
- Command line
-
hf download hf://brittlewis12/stable-code-3b-GGUF/stable-code-3b.Q8_0.gguf
-
curl -L -o stable-code-3b.Q8_0.gguf https://huggingface.co/brittlewis12/stable-code-3b-GGUF/resolve/main/stable-code-3b.Q8_0.gguf
2.97 GB
- Xet hash:
- 8285b2ac70be06cf28defcd46d6e5ee71ee792dbe15fdef30b529af2d73d5575
- Size of remote file:
- 2.97 GB
- SHA256:
- 9ecf7c8c9492806adf64d4af4630d818b7af8e09be95839a7575d5d99bb6c084
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.