Instructions to use DouraVITA/ltx-ugc-bundle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use DouraVITA/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 DouraVITA/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 type {LGraphNode} from "@comfyorg/frontend"; | |
| import type {ComfyUITestEnvironment} from "./comfyui_env"; | |
| export const PNG_1x1 = | |
| "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVQIW2P4v5ThPwAG7wKklwQ/bwAAAABJRU5ErkJggg=="; | |
| export const PNG_1x2 = | |
| "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAEAAAACCAYAAACZgbYnAAAAEElEQVQIW2NgYGD4D8QM/wEHAwH/OMSHKAAAAABJRU5ErkJggg=="; | |
| export const PNG_2x1 = | |
| "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAAIAAAABCAYAAAD0In+KAAAAD0lEQVQIW2NkYGD4D8QMAAUNAQFqjhCLAAAAAElFTkSuQmCC"; | |
| export async function pasteImageToLoadImageNode( | |
| env: ComfyUITestEnvironment, | |
| dataUrl?: string, | |
| node?: LGraphNode, | |
| ) : Promise<LGraphNode> { | |
| const dataArr = (dataUrl ?? PNG_1x1).split(","); | |
| const mime = dataArr[0]!.match(/:(.*?);/)![1]; | |
| const bstr = atob(dataArr[1]!); | |
| let n = bstr.length; | |
| const u8arr = new Uint8Array(n); | |
| while (n--) { | |
| u8arr[n] = bstr.charCodeAt(n); | |
| } | |
| const filename = `test_image_${+new Date()}.png`; | |
| const file = new File([u8arr], filename, {type: mime}); | |
| if (!node) { | |
| node = await env.addNode("LoadImage"); | |
| } | |
| await (node as any).pasteFiles([file]); | |
| let i = 0; | |
| let good = false; | |
| while (i++ < 10 || good) { | |
| good = node.widgets![0]!.value === filename; | |
| if (good) break; | |
| await env.wait(100); | |
| } | |
| if (!good) { | |
| throw new Error("Expected file not loaded."); | |
| } | |
| return node; | |
| } | |