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: 2,555 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 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | import { app } from "../../../scripts/app.js";
import { ComfyWidgets } from "../../../scripts/widgets.js";
// Displays input text on a node
// TODO: This should need to be so complicated. Refactor at some point.
app.registerExtension({
name: "pysssss.ShowText",
async beforeRegisterNodeDef(nodeType, nodeData, app) {
if (nodeData.name === "ShowText|pysssss") {
function populate(text) {
if (this.widgets) {
// On older frontend versions there is a hidden converted-widget
const isConvertedWidget = +!!this.inputs?.[0].widget;
for (let i = isConvertedWidget; i < this.widgets.length; i++) {
this.widgets[i].onRemove?.();
}
this.widgets.length = isConvertedWidget;
}
const v = [...text];
if (!v[0]) {
v.shift();
}
for (let list of v) {
// Force list to be an array, not sure why sometimes it is/isn't
if (!(list instanceof Array)) list = [list];
for (const l of list) {
const w = ComfyWidgets["STRING"](this, "text_" + this.widgets?.length ?? 0, ["STRING", { multiline: true }], app).widget;
w.inputEl.readOnly = true;
w.inputEl.style.opacity = 0.6;
w.value = l;
}
}
requestAnimationFrame(() => {
const sz = this.computeSize();
if (sz[0] < this.size[0]) {
sz[0] = this.size[0];
}
if (sz[1] < this.size[1]) {
sz[1] = this.size[1];
}
this.onResize?.(sz);
app.graph.setDirtyCanvas(true, false);
});
}
// When the node is executed we will be sent the input text, display this in the widget
const onExecuted = nodeType.prototype.onExecuted;
nodeType.prototype.onExecuted = function (message) {
onExecuted?.apply(this, arguments);
populate.call(this, message.text);
};
const VALUES = Symbol();
const configure = nodeType.prototype.configure;
nodeType.prototype.configure = function () {
// Store unmodified widget values as they get removed on configure by new frontend
this[VALUES] = arguments[0]?.widgets_values;
return configure?.apply(this, arguments);
};
const onConfigure = nodeType.prototype.onConfigure;
nodeType.prototype.onConfigure = function () {
onConfigure?.apply(this, arguments);
const widgets_values = this[VALUES];
if (widgets_values?.length) {
// In newer frontend there seems to be a delay in creating the initial widget
requestAnimationFrame(() => {
populate.call(this, widgets_values.slice(+(widgets_values.length > 1 && this.inputs?.[0].widget)));
});
}
};
}
},
});
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