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
| #!/usr/bin/env python3 | |
| import subprocess | |
| import os | |
| import re | |
| import datetime | |
| import time | |
| import argparse | |
| from __build__ import build, log_step, log_step_info | |
| _THIS_DIR = os.path.dirname(os.path.abspath(__file__)) | |
| _FILE_PY_PROJECT = os.path.join(_THIS_DIR, 'pyproject.toml') | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "-m", "--message", help="The git commit message", required=True, action="store", type=str | |
| ) | |
| args = parser.parse_args() | |
| start = time.time() | |
| build() | |
| log_step(msg='Updating version in pyproject.toml') | |
| py_project = '' | |
| with open(_FILE_PY_PROJECT, "r", encoding='utf-8') as f: | |
| py_project = f.read() | |
| version = re.search(r'^\s*version\s*=\s*"(.*?)"', py_project, flags=re.MULTILINE) | |
| version_old = version[1] | |
| now = datetime.datetime.now() | |
| version_new = version_old.split('.') | |
| version_new[-1] = f'{str(now.year)[2:]}{now.month:02}{now.day:02}{now.hour:02}{now.minute:02}' | |
| version_new = '.'.join(version_new) | |
| log_step_info(f'Updating from v{version_old} to v{version_new}') | |
| py_project = py_project.replace(version_old, version_new) | |
| with open(_FILE_PY_PROJECT, "w", encoding='utf-8') as f: | |
| f.write(py_project) | |
| log_step(status="Done") | |
| log_step('Running git add') | |
| process = subprocess.Popen(['git', 'add', '.'], stdout=subprocess.PIPE, stderr=subprocess.PIPE) | |
| stdout, stderr = process.communicate() | |
| log_step(status="Done") | |
| log_step('Running git commit') | |
| process = subprocess.Popen(['git', 'commit', '-a', '-v', '-m', args.message], | |
| stdout=subprocess.PIPE, | |
| stderr=subprocess.PIPE) | |
| stdout, stderr = process.communicate() | |
| log_step(status="Done") | |
| print(f'Finished all in {round(time.time() - start, 3)}s') | |