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
| .easyuse-prompt-styles{ | |
| overflow: auto; | |
| } | |
| .easyuse-prompt-styles .tools{ | |
| display:flex; | |
| justify-content:space-between; | |
| height:30px; | |
| padding-bottom:10px; | |
| border-bottom:2px solid var(--border-color); | |
| } | |
| .easyuse-prompt-styles .tools button.delete{ | |
| height:30px; | |
| border-radius: 8px; | |
| border: 2px solid var(--border-color); | |
| font-size:11px; | |
| background:var(--comfy-input-bg); | |
| color:var(--error-text); | |
| box-shadow:none; | |
| cursor:pointer; | |
| } | |
| .easyuse-prompt-styles .tools button.delete:hover{ | |
| filter: brightness(1.2); | |
| } | |
| .easyuse-prompt-styles .tools textarea.search{ | |
| flex:1; | |
| margin-left:10px; | |
| height:20px; | |
| line-height:20px; | |
| border-radius: 8px; | |
| border: 2px solid var(--border-color); | |
| font-size:11px; | |
| background:var(--comfy-input-bg); | |
| color:var(--input-text); | |
| box-shadow:none; | |
| padding:4px 10px; | |
| outline: none; | |
| resize: none; | |
| appearance:none; | |
| } | |
| .easyuse-prompt-styles-list{ | |
| list-style: none; | |
| padding: 0; | |
| margin: 0; | |
| min-height: 150px; | |
| height: calc(100% - 40px); | |
| overflow: auto; | |
| /*display: flex;*/ | |
| /*flex-wrap: wrap;*/ | |
| } | |
| .easyuse-prompt-styles-list.no-top{ | |
| height: auto; | |
| } | |
| .easyuse-prompt-styles-tag{ | |
| display: inline-block; | |
| vertical-align: middle; | |
| margin-top: 8px; | |
| margin-right: 8px; | |
| padding:4px; | |
| color: var(--input-text); | |
| background-color: var(--comfy-input-bg); | |
| border-radius: 8px; | |
| border: 2px solid var(--border-color); | |
| font-size:11px; | |
| cursor:pointer; | |
| } | |
| .easyuse-prompt-styles-tag.hide{ | |
| display:none; | |
| } | |
| .easyuse-prompt-styles-tag:hover{ | |
| filter: brightness(1.2); | |
| } | |
| .easyuse-prompt-styles-tag input{ | |
| --ring-color: transparent; | |
| position: relative; | |
| box-shadow: none; | |
| border: 2px solid var(--border-color); | |
| border-radius: 2px; | |
| background: linear-gradient(135deg, var(--comfy-menu-bg) 0%, var(--comfy-input-bg) 60%); | |
| } | |
| .easyuse-prompt-styles-tag input[type=checkbox]:checked{ | |
| border: 1px solid var(--theme-color-light); | |
| background-color: var(--theme-color-light); | |
| background-image: url("data:image/svg+xml,%3csvg viewBox='0 0 16 16' fill='white' xmlns='http://www.w3.org/2000/svg'%3e%3cpath d='M12.207 4.793a1 1 0 010 1.414l-5 5a1 1 0 01-1.414 0l-2-2a1 1 0 011.414-1.414L6.5 9.086l4.293-4.293a1 1 0 011.414 0z'/%3e%3c/svg%3e"); | |
| } | |
| .easyuse-prompt-styles-tag input[type=checkbox]{ | |
| color-adjust: exact; | |
| display: inline-block; | |
| flex-shrink: 0; | |
| vertical-align: middle; | |
| appearance: none; | |
| border: 2px solid var(--border-color); | |
| background-origin: border-box; | |
| padding: 0; | |
| width: 1rem; | |
| height: 1rem; | |
| border-radius:4px; | |
| color:var(--theme-color-light); | |
| user-select: none; | |
| } | |
| .easyuse-prompt-styles-tag span{ | |
| margin:0 4px; | |
| vertical-align: middle; | |
| } | |
| #show_image_id{ | |
| width:128px; | |
| height:128px; | |
| } |