Instructions to use vladmandic/Anima-1.0-Base-Merge-sdnq-hadamard-uint4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use vladmandic/Anima-1.0-Base-Merge-sdnq-hadamard-uint4 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/Anima-1.0-Base-Merge-sdnq-hadamard-uint4", 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:
- e3a3cbd3e1556be5fac0e740545c38a74932cadf4a190e2b452bf04ca429ee9e
- Size of remote file:
- 1.26 GB
- SHA256:
- ff6e9770e537712fcc23d6a24a8ec0af3a86616e9b27d6a7c8e08c30bb3e65c0
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