Instructions to use WaveCut/Anima-Preview-3-SDNQ-uint4-diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use WaveCut/Anima-Preview-3-SDNQ-uint4-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("WaveCut/Anima-Preview-3-SDNQ-uint4-diffusers", 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-uint4-diffusers 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:
- 6e17ad1932a485cfcf4d14c5e6434c90b5d11304308061f4638e96880e24472c
- Size of remote file:
- 254 MB
- SHA256:
- 3b5bf326a6c4f66fb2b2250687fdccd1f126ee7c977d2f0170cb56fdacc70a9a
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