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: 1,479 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 | import { app } from "../../../scripts/app.js";
const notificationSetup = () => {
if (!("Notification" in window)) {
console.log("This browser does not support notifications.");
alert("This browser does not support notifications.");
return;
}
if (Notification.permission === "denied") {
console.log("Notifications are blocked. Please enable them in your browser settings.");
alert("Notifications are blocked. Please enable them in your browser settings.");
return;
}
if (Notification.permission !== "granted") {
Notification.requestPermission();
}
return true;
};
app.registerExtension({
name: "pysssss.SystemNotification",
async beforeRegisterNodeDef(nodeType, nodeData, app) {
if (nodeData.name === "SystemNotification|pysssss") {
const onExecuted = nodeType.prototype.onExecuted;
nodeType.prototype.onExecuted = async function ({ message, mode }) {
onExecuted?.apply(this, arguments);
if (mode === "on empty queue") {
if (app.ui.lastQueueSize !== 0) {
await new Promise((r) => setTimeout(r, 500));
}
if (app.ui.lastQueueSize !== 0) {
return;
}
}
if (!notificationSetup()) return;
const notification = new Notification("ComfyUI", { body: message ?? "Your notification has triggered." });
};
const onNodeCreated = nodeType.prototype.onNodeCreated;
nodeType.prototype.onNodeCreated = function () {
onNodeCreated?.apply(this, arguments);
notificationSetup();
};
}
},
});
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