Instructions to use vidfom/Ltx-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use vidfom/Ltx-3 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="vidfom/Ltx-3", filename="ComfyUI/models/text_encoders/gemma-3-12b-it-qat-UD-Q4_K_XL.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 vidfom/Ltx-3 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
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 vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
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 vidfom/Ltx-3:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf vidfom/Ltx-3:UD-Q4_K_XL
Use Docker
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use vidfom/Ltx-3 with Ollama:
ollama run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Unsloth Studio
How to use vidfom/Ltx-3 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 vidfom/Ltx-3 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 vidfom/Ltx-3 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vidfom/Ltx-3 to start chatting
- Docker Model Runner
How to use vidfom/Ltx-3 with Docker Model Runner:
docker model run hf.co/vidfom/Ltx-3:UD-Q4_K_XL
- Lemonade
How to use vidfom/Ltx-3 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull vidfom/Ltx-3:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Ltx-3-UD-Q4_K_XL
List all available models
lemonade list
| .pysssss-workflow-popup{ | |
| min-width:220px; | |
| /*right:0px!important;*/ | |
| /*left:auto!important;*/ | |
| } | |
| body{ | |
| font-family: var(--font-family); | |
| -webkit-font-smoothing: antialiased; | |
| -moz-osx-font-smoothing: grayscale; | |
| } | |
| textarea{ | |
| font-family: var(--font-family); | |
| } | |
| .comfy-multiline-input{ | |
| background-color: transparent; | |
| border:1px solid var(--border-color); | |
| border-radius:8px; | |
| padding: 8px; | |
| font-size: 12px; | |
| } | |
| .comfy-modal { | |
| border:1px solid var(--border-color); | |
| box-shadow:none; | |
| backdrop-filter: blur(8px) brightness(120%); | |
| } | |
| .comfy-menu{ | |
| border-radius:16px; | |
| box-shadow:0 0 1px var(--descrip-text); | |
| backdrop-filter: blur(8px) brightness(120%); | |
| } | |
| .comfy-menu button,.comfy-modal button { | |
| font-size: 14px; | |
| padding:4px 0; | |
| margin-bottom:4px; | |
| } | |
| .comfy-menu button.comfy-settings-btn{ | |
| font-size: 12px; | |
| } | |
| .comfy-menu-btns { | |
| margin-bottom: 4px; | |
| } | |
| .comfy-menu-btns button,.comfy-list-actions button{ | |
| font-size: 10px; | |
| } | |
| .comfy-menu > button, | |
| .comfy-menu-btns button, | |
| .comfy-menu .comfy-list button, | |
| .comfy-modal button { | |
| border-width:1px; | |
| } | |
| .comfy-modal-content{ | |
| width: 100%; | |
| } | |
| dialog{ | |
| border:1px solid var(--border-color); | |
| background:transparent; | |
| backdrop-filter: blur(8px) brightness(120%); | |
| box-shadow:none; | |
| } | |
| .cm-title{ | |
| background-color:transparent; | |
| } | |
| .cm-notice-board{ | |
| border-radius:10px; | |
| border:1px solid var(--border-color); | |
| } | |
| .cm-menu-container{ | |
| margin-bottom:50px; | |
| } | |
| hr{ | |
| border:1px solid var(--border-color); | |
| } | |
| #comfy-dev-save-api-button{ | |
| justify-content: center; | |
| } | |
| #shareButton{ | |
| background:linear-gradient(to left,var(--theme-color),var(--theme-color-light)); | |
| color:white; | |
| } | |
| #queue-button{ | |
| position:relative; | |
| overflow:hidden; | |
| min-height:30px; | |
| z-index:1; | |
| } | |
| #queue-button:after{ | |
| clear: both; | |
| content:attr(data-attr); | |
| background:green; | |
| color:#FFF; | |
| width:var(--process-bar-width); | |
| height:100%; | |
| position:absolute; | |
| top:0; | |
| left:0; | |
| z-index:0; | |
| text-align:center; | |
| display:flex; | |
| justify-content:center; | |
| align-items:center; | |
| } | |
| .litegraph .litemenu-entry.has_submenu { | |
| border-right: 2px solid var(--theme-color); | |
| } | |
| ::-webkit-scrollbar { | |
| width: 0em; | |
| } | |
| ::-webkit-scrollbar-track { | |
| background-color: transparent; | |
| } | |
| ::-webkit-scrollbar-thumb { | |
| background-color: transparent; | |
| border-radius: 2px; | |
| } | |
| ::-webkit-scrollbar-thumb:hover { | |
| background-color: transparent; | |
| } | |
| [data-theme="dark"] .workspace_manager .chakra-card{ | |
| background-color:var(--comfy-menu-bg); | |
| } | |
| .workspace_manager .chakra-card{ | |
| width: 400px; | |
| } |