Instructions to use Wizz13150/WizzGPTv6 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 Wizz13150/WizzGPTv6 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 Wizz13150/WizzGPTv6:Q8_0 # Run inference directly in the terminal: llama cli -hf Wizz13150/WizzGPTv6:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Wizz13150/WizzGPTv6:Q8_0 # Run inference directly in the terminal: llama cli -hf Wizz13150/WizzGPTv6:Q8_0
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 Wizz13150/WizzGPTv6:Q8_0 # Run inference directly in the terminal: ./build/bin/llama cli -hf Wizz13150/WizzGPTv6:Q8_0
Use Docker
docker model run hf.co/Wizz13150/WizzGPTv6:Q8_0
- Llama new
- LM Studio
- Jan
- Ollama
How to use Wizz13150/WizzGPTv6 with Ollama:
ollama run hf.co/Wizz13150/WizzGPTv6:Q8_0
- Unsloth Desktop
- Docker Model Runner
How to use Wizz13150/WizzGPTv6 with Docker Model Runner:
docker model run hf.co/Wizz13150/WizzGPTv6:Q8_0
- Lemonade
How to use Wizz13150/WizzGPTv6 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Wizz13150/WizzGPTv6:Q8_0
Run and chat with the model
lemonade run user.WizzGPTv6-Q8_0
List all available models
lemonade list
- Atomic Chat
Download pytorch_model.bin from Wizz13150/WizzGPTv6: direct link, hf CLI and curl.
- Browser
- Download file 498 MB
-
https://huggingface.co/Wizz13150/WizzGPTv6/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Wizz13150/WizzGPTv6/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Wizz13150/WizzGPTv6/resolve/main/pytorch_model.bin
498 MB
- Xet hash:
- 6ef0fd7f2bb5e6c501258fac075c29f48e7de7fd8590bcfc15c3b1d3ce69fd6b
- Size of remote file:
- 498 MB
- SHA256:
- 7a461dc7e1a55053b2f463f8c7f2145e8ed608a4aa54ccdf6b4bbc5198bc81c5
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