Instructions to use itsdotscience/Magicoder-S-DS-6.7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use itsdotscience/Magicoder-S-DS-6.7B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="itsdotscience/Magicoder-S-DS-6.7B-GGUF", filename="Magicoder-S-DS-6.7B_q8_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use itsdotscience/Magicoder-S-DS-6.7B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0 # Run inference directly in the terminal: llama-cli -hf itsdotscience/Magicoder-S-DS-6.7B-GGUF: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 itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf itsdotscience/Magicoder-S-DS-6.7B-GGUF: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 itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0
Use Docker
docker model run hf.co/itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0
- LM Studio
- Jan
- Ollama
How to use itsdotscience/Magicoder-S-DS-6.7B-GGUF with Ollama:
ollama run hf.co/itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0
- Unsloth Studio new
How to use itsdotscience/Magicoder-S-DS-6.7B-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 itsdotscience/Magicoder-S-DS-6.7B-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 itsdotscience/Magicoder-S-DS-6.7B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for itsdotscience/Magicoder-S-DS-6.7B-GGUF to start chatting
- Docker Model Runner
How to use itsdotscience/Magicoder-S-DS-6.7B-GGUF with Docker Model Runner:
docker model run hf.co/itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0
- Lemonade
How to use itsdotscience/Magicoder-S-DS-6.7B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull itsdotscience/Magicoder-S-DS-6.7B-GGUF:Q8_0
Run and chat with the model
lemonade run user.Magicoder-S-DS-6.7B-GGUF-Q8_0
List all available models
lemonade list
Please provide 4 bit, Thank you.
I also would like to have Q6_K or Q5_K_M as a great balance between size and performance (Q4 can be a bit rough around the edges at this model size)
Actually you can do it yourself (although it's not recommended for already quantized models) with llama.cpp. Just build llama.cpp from source and then run:
(llama.cpp)$ ./quantize --allow-requantize Magicoder-S-DS-6.7B_q8_0.gguf <output_requantized_model>.gguf q4_k_m
any 4 bit good quants yet?
I just uploaded a q3, q4 and q5 here https://huggingface.co/matthoffner/Magicoder-S-DS-6.7B-GGUF/tree/main
I just uploaded a q3, q4 and q5 here https://huggingface.co/matthoffner/Magicoder-S-DS-6.7B-GGUF/tree/main
Hey thanks, i ended up( merging 417884e regex_gpt2_preprocess pr and it works) , wonder if this will produce any better results or otherwise.
It seems to work ok so far, I set up a space with it here https://huggingface.co/spaces/matthoffner/ggml-coding-llm