Image-to-Video
Diffusers
text-to-video
video-to-video
image-text-to-video
audio-to-video
text-to-audio
video-to-audio
audio-to-audio
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
ltx-2
ltx-2-3
ltx-video
ltxv
lightricks
Eval Results
Instructions to use Lightricks/LTX-2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lightricks/LTX-2.3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2.3", torch_dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
LTX-2.3
#58
by R4PTORINF1LTR - opened
README.md
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# Run locally
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## Direct use license
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You can use the models - full, distilled, upscalers and any derivatives of the models - for purposes under the [license](
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## ComfyUI
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We recommend you use the built-in LTXVideo nodes that can be found in the ComfyUI Manager.
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# Run locally
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## Direct use license
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You can use the models - full, distilled, upscalers and any derivatives of the models - for purposes under the [license](./LICENSE).
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## ComfyUI
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We recommend you use the built-in LTXVideo nodes that can be found in the ComfyUI Manager.
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