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
| class ShowText: | |
| def INPUT_TYPES(s): | |
| return { | |
| "required": { | |
| "text": ("STRING", {"forceInput": True}), | |
| }, | |
| "hidden": { | |
| "unique_id": "UNIQUE_ID", | |
| "extra_pnginfo": "EXTRA_PNGINFO", | |
| }, | |
| } | |
| INPUT_IS_LIST = True | |
| RETURN_TYPES = ("STRING",) | |
| FUNCTION = "notify" | |
| OUTPUT_NODE = True | |
| OUTPUT_IS_LIST = (True,) | |
| CATEGORY = "utils" | |
| def notify(self, text, unique_id=None, extra_pnginfo=None): | |
| if unique_id is not None and extra_pnginfo is not None: | |
| if not isinstance(extra_pnginfo, list): | |
| print("Error: extra_pnginfo is not a list") | |
| elif ( | |
| not isinstance(extra_pnginfo[0], dict) | |
| or "workflow" not in extra_pnginfo[0] | |
| ): | |
| print("Error: extra_pnginfo[0] is not a dict or missing 'workflow' key") | |
| else: | |
| workflow = extra_pnginfo[0]["workflow"] | |
| node = next( | |
| (x for x in workflow["nodes"] if str(x["id"]) == str(unique_id[0])), | |
| None, | |
| ) | |
| if node: | |
| node["widgets_values"] = [text] | |
| return {"ui": {"text": text}, "result": (text,)} | |
| NODE_CLASS_MAPPINGS = { | |
| "ShowText|pysssss": ShowText, | |
| } | |
| NODE_DISPLAY_NAME_MAPPINGS = { | |
| "ShowText|pysssss": "Show Text 🐍", | |
| } | |