Instructions to use hgjc/ltx-ugc-bundle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use hgjc/ltx-ugc-bundle with LTX.io:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --frozen
# Download the weights from this repo, plus the Gemma text encoder hf download hgjc/ltx-ugc-bundle --local-dir models/ltx-ugc-bundle hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Fast pipeline (distilled model, no distilled LoRA needed) uv run python -m ltx_pipelines.distilled \ --distilled-checkpoint-path models/ltx-ugc-bundle/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/ltx-ugc-bundle/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# HQ pipeline (two-stage, higher quality) uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path models/ltx-ugc-bundle/<checkpoint>.safetensors \ --distilled-lora models/ltx-ugc-bundle/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/ltx-ugc-bundle/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
| import { api } from "../../../scripts/api.js"; | |
| import { app } from "../../../scripts/app.js"; | |
| // Simple script that adds the current queue size to the window title | |
| // Adds a favicon that changes color while active | |
| app.registerExtension({ | |
| name: "pysssss.FaviconStatus", | |
| async setup() { | |
| let link = document.querySelector("link[rel~='icon']"); | |
| if (!link) { | |
| link = document.createElement("link"); | |
| link.rel = "icon"; | |
| document.head.appendChild(link); | |
| } | |
| const getUrl = (active, user) => new URL(`assets/favicon${active ? "-active" : ""}${user ? ".user" : ""}.ico`, import.meta.url); | |
| const testUrl = async (active) => { | |
| const url = getUrl(active, true); | |
| const r = await fetch(url, { | |
| method: "HEAD", | |
| }); | |
| if (r.status === 200) { | |
| return url; | |
| } | |
| return getUrl(active, false); | |
| }; | |
| const activeUrl = await testUrl(true); | |
| const idleUrl = await testUrl(false); | |
| let executing = false; | |
| const update = () => (link.href = executing ? activeUrl : idleUrl); | |
| for (const e of ["execution_start", "progress"]) { | |
| api.addEventListener(e, () => { | |
| executing = true; | |
| update(); | |
| }); | |
| } | |
| api.addEventListener("executing", ({ detail }) => { | |
| // null will be sent when it's finished | |
| executing = !!detail; | |
| update(); | |
| }); | |
| api.addEventListener("status", ({ detail }) => { | |
| let title = "ComfyUI"; | |
| if (detail && detail.exec_info.queue_remaining) { | |
| title = `(${detail.exec_info.queue_remaining}) ${title}`; | |
| } | |
| document.title = title; | |
| update(); | |
| executing = false; | |
| }); | |
| update(); | |
| }, | |
| }); | |