Instructions to use vladmandic/longanimatediff-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vladmandic/longanimatediff-64 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("vladmandic/longanimatediff-64", 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
- Xet hash:
- cdce3306d008c29837bd2f122d87efe044bc7235995828e3ef29a759e7454028
- Size of remote file:
- 1.83 GB
- SHA256:
- 0a9edca4b9479e01401c73088d721822153f48cbc5a7e255596dfed32c845798
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