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"; | |
| const id = "pysssss.UseNumberInputPrompt"; | |
| const ext = { | |
| name: id, | |
| async setup(app) { | |
| const prompt = LGraphCanvas.prototype.prompt; | |
| const setting = app.ui.settings.addSetting({ | |
| id, | |
| name: "🐍 Use number input on value entry", | |
| defaultValue: false, | |
| type: "boolean", | |
| }); | |
| LGraphCanvas.prototype.prompt = function () { | |
| const dialog = prompt.apply(this, arguments); | |
| if (setting.value && typeof arguments[1] === "number") { | |
| // If this should be a number then update the imput | |
| const input = dialog.querySelector("input"); | |
| input.type = "number"; | |
| // Add constraints | |
| const widget = app.canvas.node_widget?.[1]; | |
| if (widget?.options) { | |
| for (const prop of ["min", "max", "step"]) { | |
| if (widget.options[prop]) input[prop] = widget.options[prop]; | |
| } | |
| } | |
| } | |
| return dialog; | |
| }; | |
| }, | |
| }; | |
| app.registerExtension(ext); | |