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
still crash the faces
4
#2 opened about 1 month ago
by
ZKong
How do users determine which lora to use?
1
#1 opened about 1 month ago
by
wencx