Text-to-Video
Diffusers
Safetensors
modular_diffusers
vae
ltx2.3
lightricks
video-to-video
text-to-audio
Instructions to use AINovice2005/pruna-vaed-modular-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AINovice2005/pruna-vaed-modular-diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("AINovice2005/pruna-vaed-modular-diffusers", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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# Pruna VAE for Modular Diffusers
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This repository provides a **Modular Diffusers** implementation of
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the model as a reusable Modular Diffusers component.
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The repository exposes a custom `LoadPrunaVAE` block that downloads and instantiates `PrunaAutoencoderKLLTX2Video`, making it available as `components.vae` within a Modular Diffusers pipeline.
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## Acknowledgements
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This work builds upon the Pruna VAE implementation released by **PrunaAI** and adapts it for use as a reusable Modular Diffusers component.
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# Pruna VAE for Modular Diffusers
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This repository provides a **Modular Diffusers** implementation of [PrunaVAED](https://huggingface.co/PrunaAI/PrunaVAED). It packages the optimized video decoder implementation together with the custom loading mechanism required to use
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the model as a reusable Modular Diffusers component.
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The repository exposes a custom `LoadPrunaVAE` block that downloads and instantiates `PrunaAutoencoderKLLTX2Video`, making it available as `components.vae` within a Modular Diffusers pipeline.
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## Acknowledgements
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This work builds upon the Pruna VAE implementation released by **[PrunaAI](https://github.com/PrunaAI/pruna)** and adapts it for use as a reusable Modular Diffusers component.
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