Instructions to use FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/FastWan2.2-TI2V-5B-FullAttn-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("FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers", 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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## Introduction
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We're excited to introduce the **FastWan2.2 series**—a new line of models finetuned with our novel **Sparse-distill** strategy. This approach jointly integrates DMD and VSA in a single training process, combining the benefits of both **distillation** to shorten diffusion steps and **sparse attention** to reduce attention computations, enabling even faster video generation.
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FastWan2.2-TI2V-5B-Diffusers is built upon Wan-AI/Wan2.2-TI2V-5B-Diffusers. It supports efficient **3-step inference** and produces high-quality videos at 121×704×1280 resolution. For training, we used simulated forward for the generator model, making the process data-free. The current FastWan2.2-TI2V-5B-Diffusers model is trained using only DMD.
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## Introduction
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We're excited to introduce the **FastWan2.2 series**—a new line of models finetuned with our novel **Sparse-distill** strategy. This approach jointly integrates DMD and VSA in a single training process, combining the benefits of both **distillation** to shorten diffusion steps and **sparse attention** to reduce attention computations, enabling even faster video generation.
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FastWan2.2-TI2V-5B-Diffusers is built upon Wan-AI/Wan2.2-TI2V-5B-Diffusers. It supports efficient **3-step inference** and produces high-quality videos at 121×704×1280 resolution. For training, we used simulated forward for the generator model, making the process data-free. **The current FastWan2.2-TI2V-5B-Diffusers model is trained using only DMD**.
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