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
| from .src.comfymath.convert import NODE_CLASS_MAPPINGS as convert_NCM | |
| from .src.comfymath.bool import NODE_CLASS_MAPPINGS as bool_NCM | |
| from .src.comfymath.int import NODE_CLASS_MAPPINGS as int_NCM | |
| from .src.comfymath.float import NODE_CLASS_MAPPINGS as float_NCM | |
| from .src.comfymath.number import NODE_CLASS_MAPPINGS as number_NCM | |
| from .src.comfymath.vec import NODE_CLASS_MAPPINGS as vec_NCM | |
| from .src.comfymath.control import NODE_CLASS_MAPPINGS as control_NCM | |
| from .src.comfymath.graphics import NODE_CLASS_MAPPINGS as graphics_NCM | |
| NODE_CLASS_MAPPINGS = { | |
| **convert_NCM, | |
| **bool_NCM, | |
| **int_NCM, | |
| **float_NCM, | |
| **number_NCM, | |
| **vec_NCM, | |
| **control_NCM, | |
| **graphics_NCM, | |
| } | |
| def remove_cm_prefix(node_mapping: str) -> str: | |
| if node_mapping.startswith("CM_"): | |
| return node_mapping[3:] | |
| return node_mapping | |
| NODE_DISPLAY_NAME_MAPPINGS = {key: remove_cm_prefix(key) for key in NODE_CLASS_MAPPINGS} | |