Image-to-Video
Diffusers
LTX-2
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-video
ltxv
lightricks
ltx-2.3
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", 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") - LTX-2
How to use Lightricks/LTX-2.3 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 Lightricks/LTX-2.3 --local-dir models/LTX-2.3 hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Fast pipeline (distilled model, no distilled LoRA needed) uv run python -m ltx_pipelines.distilled \ --distilled-checkpoint-path models/LTX-2.3/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/LTX-2.3/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# HQ pipeline (two-stage, higher quality) uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path models/LTX-2.3/<checkpoint>.safetensors \ --distilled-lora models/LTX-2.3/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/LTX-2.3/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
json file reuired for this model is missing
#69
by mahendra0120 - opened
- README.md +2 -2
- ltx-2.3-spatial-upscaler-x2-1.0.safetensors +3 -0
README.md
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library_name: diffusers
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license: other
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license_name: ltx-2-community-license-agreement
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license_link: https://github.com/Lightricks/LTX-2/blob/main/LICENSE
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pipeline_tag: image-to-video
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arxiv: 2601.03233
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tags:
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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](https://github.com/Lightricks/LTX-2/blob/main/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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library_name: diffusers
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license: other
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license_name: ltx-2-community-license-agreement
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license_link: https://github.com/Lightricks/LTX-2/blob/main/LICENSE
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pipeline_tag: image-to-video
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arxiv: 2601.03233
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tags:
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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](https://github.com/Lightricks/LTX-2/blob/main/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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ltx-2.3-spatial-upscaler-x2-1.0.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:93800de87dbc448b5b31f3c5c3a1579ba6335151de061a564f6f026b0fc770ad
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size 995743504
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