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 { app } from "../../../scripts/app.js"; | |
| app.registerExtension({ | |
| name: "pysssss.GraphArrange", | |
| setup(app) { | |
| const orig = LGraphCanvas.prototype.getCanvasMenuOptions; | |
| LGraphCanvas.prototype.getCanvasMenuOptions = function () { | |
| const options = orig.apply(this, arguments); | |
| options.push({ content: "Arrange (float left)", callback: () => graph.arrange() }); | |
| options.push({ | |
| content: "Arrange (float right)", | |
| callback: () => { | |
| (function () { | |
| var margin = 50; | |
| var layout; | |
| const nodes = this.computeExecutionOrder(false, true); | |
| const columns = []; | |
| // Find node first use | |
| for (let i = nodes.length - 1; i >= 0; i--) { | |
| const node = nodes[i]; | |
| let max = null; | |
| for (const out of node.outputs || []) { | |
| if (out.links) { | |
| for (const link of out.links) { | |
| const outNode = app.graph.getNodeById(app.graph.links[link].target_id); | |
| if (!outNode) continue; | |
| var l = outNode._level - 1; | |
| if (max === null) max = l; | |
| else if (l < max) max = l; | |
| } | |
| } | |
| } | |
| if (max != null) node._level = max; | |
| } | |
| for (let i = 0; i < nodes.length; ++i) { | |
| const node = nodes[i]; | |
| const col = node._level || 1; | |
| if (!columns[col]) { | |
| columns[col] = []; | |
| } | |
| columns[col].push(node); | |
| } | |
| let x = margin; | |
| for (let i = 0; i < columns.length; ++i) { | |
| const column = columns[i]; | |
| if (!column) { | |
| continue; | |
| } | |
| column.sort((a, b) => { | |
| var as = !(a.type === "SaveImage" || a.type === "PreviewImage"); | |
| var bs = !(b.type === "SaveImage" || b.type === "PreviewImage"); | |
| var r = as - bs; | |
| if (r === 0) r = (a.inputs?.length || 0) - (b.inputs?.length || 0); | |
| if (r === 0) r = (a.outputs?.length || 0) - (b.outputs?.length || 0); | |
| return r; | |
| }); | |
| let max_size = 100; | |
| let y = margin + LiteGraph.NODE_TITLE_HEIGHT; | |
| for (let j = 0; j < column.length; ++j) { | |
| const node = column[j]; | |
| node.pos[0] = layout == LiteGraph.VERTICAL_LAYOUT ? y : x; | |
| node.pos[1] = layout == LiteGraph.VERTICAL_LAYOUT ? x : y; | |
| const max_size_index = layout == LiteGraph.VERTICAL_LAYOUT ? 1 : 0; | |
| if (node.size[max_size_index] > max_size) { | |
| max_size = node.size[max_size_index]; | |
| } | |
| const node_size_index = layout == LiteGraph.VERTICAL_LAYOUT ? 0 : 1; | |
| y += node.size[node_size_index] + margin + LiteGraph.NODE_TITLE_HEIGHT + j; | |
| } | |
| // Right align in column | |
| for (let j = 0; j < column.length; ++j) { | |
| const node = column[j]; | |
| node.pos[0] += max_size - node.size[0]; | |
| } | |
| x += max_size + margin; | |
| } | |
| this.setDirtyCanvas(true, true); | |
| }).apply(app.graph); | |
| }, | |
| }); | |
| return options; | |
| }; | |
| }, | |
| }); | |