Image-to-Video
LTX.io
lora
ic-lora
ltx-video
ltx-2.3
video
video-to-video
3d-to-real
render-to-real
photorealistic
cgi
fal
Instructions to use fal/LTX-2.3-3DREAL-LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use fal/LTX-2.3-3DREAL-LoRA 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 fal/LTX-2.3-3DREAL-LoRA --local-dir models/LTX-2.3-3DREAL-LoRA 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-2.3-3DREAL-LoRA/<weights>.safetensors 1.0 \ --video-conditioning reference.mp4 1.0 \ --prompt "your prompt here" \ --output-path output.mp4 - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- b137b78f4c00ea1bc06b36e0644722cd926c67d34f83a382e484ce337c1c0c88
- Size of remote file:
- 5.28 MB
- SHA256:
- d3d44ae51d8514ac441a0aaabed8719fe105158770fd7568c7741cc69819ca6d
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