Instructions to use Lightricks/LTX-2.3-22b-IC-LoRA-Pixel-Spatial-Upscaler with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use Lightricks/LTX-2.3-22b-IC-LoRA-Pixel-Spatial-Upscaler 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 Lightricks/LTX-2.3-22b-IC-LoRA-Pixel-Spatial-Upscaler --local-dir models/LTX-2.3-22b-IC-LoRA-Pixel-Spatial-Upscaler hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Video-to-video with the IC-LoRA (runs on the distilled base model) uv run python -m ltx_pipelines.ic_lora \ --distilled-checkpoint-path path/to/distilled_checkpoint.safetensors \ --spatial-upsampler-path path/to/spatial_upsampler.safetensors \ --gemma-root models/gemma-3-12b \ --lora models/LTX-2.3-22b-IC-LoRA-Pixel-Spatial-Upscaler/<weights>.safetensors 1.0 \ --video-conditioning reference.mp4 1.0 \ --prompt "your prompt here" \ --output-path output.mp4 - Notebooks
- Google Colab
- Kaggle
How do users determine which lora to use?
#1
by wencx - opened
For example, if a video is 480p and enlarged to 720p, what is the difference between using x2 and x4?
For example, if a video is 480p and enlarged to 720p, what is the difference between using x2 and x4?
You choose based on your input video resolution, desired output resolution and your patience. x4 will be much slower to achieve not to mention RAM/VRAM constraints. IC-Lora requires/implies a guide so it will takes its time.