Instructions to use sangoi-exe/sd-webui-codex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use sangoi-exe/sd-webui-codex with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="sangoi-exe/sd-webui-codex", filename="flux-tenc/t5xxl.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 sangoi-exe/sd-webui-codex with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sangoi-exe/sd-webui-codex:Q4_K_M # Run inference directly in the terminal: llama-cli -hf sangoi-exe/sd-webui-codex:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf sangoi-exe/sd-webui-codex:Q4_K_M # Run inference directly in the terminal: llama-cli -hf sangoi-exe/sd-webui-codex:Q4_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 sangoi-exe/sd-webui-codex:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf sangoi-exe/sd-webui-codex:Q4_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 sangoi-exe/sd-webui-codex:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf sangoi-exe/sd-webui-codex:Q4_K_M
Use Docker
docker model run hf.co/sangoi-exe/sd-webui-codex:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use sangoi-exe/sd-webui-codex with Ollama:
ollama run hf.co/sangoi-exe/sd-webui-codex:Q4_K_M
- Unsloth Studio new
How to use sangoi-exe/sd-webui-codex 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 sangoi-exe/sd-webui-codex 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 sangoi-exe/sd-webui-codex to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for sangoi-exe/sd-webui-codex to start chatting
- Docker Model Runner
How to use sangoi-exe/sd-webui-codex with Docker Model Runner:
docker model run hf.co/sangoi-exe/sd-webui-codex:Q4_K_M
- Lemonade
How to use sangoi-exe/sd-webui-codex with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull sangoi-exe/sd-webui-codex:Q4_K_M
Run and chat with the model
lemonade run user.sd-webui-codex-Q4_K_M
List all available models
lemonade list
Do you plan to upload Text Encoders etc?
Hello!
I'm having some issues w/ inferencing that might be related to having mismatching text encoder files for Z-Image(etc). Are you planning to eventually upload all of the components needed? Or can you advise which I should use for Z-Image/SDXL/Wan Re:
https://github.com/sangoi-exe/stable-diffusion-webui-codex/issues/5
https://github.com/sangoi-exe/stable-diffusion-webui-codex/issues/4
Thanks for your efforts on this project - it looks really sleek and I hope you continue to modernize it w/ the latest models!!
Hello! It was a oversight tbh, I had it and forgot to upload π I've just uploaded it
Thanks, btw, atm I'm implementing the LTX2.3 on dev branch π
Thanks for your help, and building a really cool app! I'm excited to see where you take it!