Instructions to use bionicman69/StarTrek_TNG_Style_LTX23 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX-2
How to use bionicman69/StarTrek_TNG_Style_LTX23 with LTX-2:
# 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
- Xet hash:
- 508fab20bad1e83cbc72c7a458e1fded9de63f7805af796bcfaf76a9fe22bfff
- Size of remote file:
- 36.5 MB
- SHA256:
- 2da067a17266f7180c03951ac69e76fd29468a398bd6ece3e64cb2593b57e947
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.