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: 937 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 | 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}
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