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
File size: 1,500 Bytes
46dc982 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 | import { app } from "../../../scripts/app.js";
app.registerExtension({
name: "pysssss.KSamplerAdvDenoise",
async beforeRegisterNodeDef(nodeType) {
// Add menu options to conver to/from widgets
const origGetExtraMenuOptions = nodeType.prototype.getExtraMenuOptions;
nodeType.prototype.getExtraMenuOptions = function (_, options) {
const r = origGetExtraMenuOptions?.apply?.(this, arguments);
let stepsWidget = null;
let startAtWidget = null;
let endAtWidget = null;
for (const w of this.widgets || []) {
if (w.name === "steps") {
stepsWidget = w;
} else if (w.name === "start_at_step") {
startAtWidget = w;
} else if (w.name === "end_at_step") {
endAtWidget = w;
}
}
if (stepsWidget && startAtWidget && endAtWidget) {
options.push(
{
content: "Set Denoise",
callback: () => {
const steps = +prompt("How many steps do you want?", 15);
if (isNaN(steps)) {
return;
}
const denoise = +prompt("How much denoise? (0-1)", 0.5);
if (isNaN(denoise)) {
return;
}
stepsWidget.value = Math.floor(steps / Math.max(0, Math.min(1, denoise)));
stepsWidget.callback?.(stepsWidget.value);
startAtWidget.value = stepsWidget.value - steps;
startAtWidget.callback?.(startAtWidget.value);
endAtWidget.value = stepsWidget.value;
endAtWidget.callback?.(endAtWidget.value);
},
},
null
);
}
return r;
};
},
});
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