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 Settings
- 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
| /** | |
| * Attaches metadata to the workflow on save | |
| * - custom node pack version to all custom nodes used in the workflow | |
| * | |
| * Example metadata: | |
| * "nodes": { | |
| * "1": { | |
| * type: "CheckpointLoaderSimple", | |
| * ... | |
| * properties: { | |
| * cnr_id: "comfy-core", | |
| * version: "0.3.8", | |
| * }, | |
| * }, | |
| * } | |
| * | |
| * @typedef {Object} NodeInfo | |
| * @property {string} ver - Version (git hash or semantic version) | |
| * @property {string} cnr_id - ComfyRegistry node ID | |
| * @property {boolean} enabled - Whether the node is enabled | |
| */ | |
| import { app } from "../../scripts/app.js"; | |
| import { api } from "../../scripts/api.js"; | |
| class WorkflowMetadataExtension { | |
| constructor() { | |
| this.name = "Comfy.CustomNodesManager.WorkflowMetadata"; | |
| this.installedNodes = {}; | |
| this.comfyCoreVersion = null; | |
| } | |
| /** | |
| * Get the installed nodes info | |
| * @returns {Promise<Record<string, NodeInfo>>} The mapping from node name to its info. | |
| * ver can either be a git commit hash or a semantic version such as "1.0.0" | |
| * cnr_id is the id of the node in the ComfyRegistry | |
| * enabled is true if the node is enabled, false if it is disabled | |
| */ | |
| async getInstalledNodes() { | |
| const res = await api.fetchApi("/customnode/installed"); | |
| return await res.json(); | |
| } | |
| async init() { | |
| this.installedNodes = await this.getInstalledNodes(); | |
| this.comfyCoreVersion = (await api.getSystemStats()).system.comfyui_version; | |
| } | |
| /** | |
| * Called when any node is created | |
| * @param {LGraphNode} node The newly created node | |
| */ | |
| nodeCreated(node) { | |
| try { | |
| // nodeData doesn't exist if node is missing or node is frontend only node | |
| if (!node?.constructor?.nodeData?.python_module) return; | |
| const nodeProperties = (node.properties ??= {}); | |
| const modules = node.constructor.nodeData.python_module.split("."); | |
| const moduleType = modules[0]; | |
| if (moduleType === "custom_nodes") { | |
| const nodePackageName = modules[1]; | |
| const { cnr_id, aux_id, ver } = | |
| this.installedNodes[nodePackageName] ?? | |
| this.installedNodes[nodePackageName.toLowerCase()] ?? | |
| {}; | |
| if (cnr_id === "comfy-core") return; // don't allow hijacking comfy-core name | |
| if (cnr_id) nodeProperties.cnr_id = cnr_id; | |
| else nodeProperties.aux_id = aux_id; | |
| if (ver) nodeProperties.ver = ver.trim(); | |
| } else if (["nodes", "comfy_extras", "comfy_api_nodes"].includes(moduleType)) { | |
| nodeProperties.cnr_id = "comfy-core"; | |
| nodeProperties.ver = this.comfyCoreVersion; | |
| } | |
| } catch (e) { | |
| console.error(e); | |
| } | |
| } | |
| } | |
| app.registerExtension(new WorkflowMetadataExtension()); | |