Instructions to use bionicman69/StarTrek_TNG_Style_LTX23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use bionicman69/StarTrek_TNG_Style_LTX23 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 bionicman69/StarTrek_TNG_Style_LTX23 --local-dir models/StarTrek_TNG_Style_LTX23 hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Text/image-to-video with the LoRA on the HQ two-stage base pipeline uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path path/to/checkpoint.safetensors \ --distilled-lora path/to/distilled_lora.safetensors 0.8 \ --spatial-upsampler-path path/to/spatial_upsampler.safetensors \ --gemma-root models/gemma-3-12b \ --lora models/StarTrek_TNG_Style_LTX23/<weights>.safetensors 1.0 \ --prompt "your prompt here" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
Rename LTX_2.3__0dio.mp4 to beverlycrusher.mp4
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- LTX_2.3__0dio.mp4 → beverlycrusher.mp4 +0 -0
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