Text-to-Image
Diffusers
Safetensors
Cosmos
AnimaTextToImagePipeline
sdnq
anima
uint4
8-bit precision
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 Settings
- Draw Things
- DiffusionBee
- Xet hash:
- f2859427ff1504e2b0ef63ed38945447606b1de5f70d1dff9a7480274a7d7005
- Size of remote file:
- 269 MB
- SHA256:
- 55f9e57ad9e98f7074fb7b3bd60896de4e55f1fe98037d2ffce55242ecb245f1
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