Instructions to use WaveCut/Anima-Preview-3-SDNQ-int8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Anima-Preview-3-SDNQ-int8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("WaveCut/Anima-Preview-3-SDNQ-int8", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Cosmos
How to use WaveCut/Anima-Preview-3-SDNQ-int8 with Cosmos:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee

- Xet hash:
- 13929fb318960626cc3fe3070ec4b1fd6a207d33bff5989611e6aef646657f89
- Size of remote file:
- 4.02 MB
- SHA256:
- d908c9ac7a81c3decd66b86aaec1eff4405ab774e1d9e8884e3f2ab1de07c909
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