Instructions to use thu-ml/Hunyuan-RIFLEx-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use thu-ml/Hunyuan-RIFLEx-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("thu-ml/Hunyuan-RIFLEx-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
Add link to code
Browse filesThis PR adds a link to the Github repository, making it easier for people to find the code.
README.md
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license: apache-2.0
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pipeline_tag: text-to-video
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library_name: diffusers
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# RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers
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Project page: https://riflex-video.github.io/
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## 🎉 Supported Models
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Here, we list the SOTA video diffusion transformers that RIFLEx has been applied to. We are continuously working to support more models. Feel free to suggest additional models you would like us to support!
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library_name: diffusers
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license: apache-2.0
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pipeline_tag: text-to-video
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# RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers
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Project page: https://riflex-video.github.io/
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For code, see https://github.com/thu-ml/RIFLEx.
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## 🎉 Supported Models
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Here, we list the SOTA video diffusion transformers that RIFLEx has been applied to. We are continuously working to support more models. Feel free to suggest additional models you would like us to support!
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