Instructions to use Masterjp123/AnythingV5Nijimix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Masterjp123/AnythingV5Nijimix with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Masterjp123/AnythingV5Nijimix", 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:
- 0e4415b7f8b5571e51981f9898016121890e32c8ec3105ac1abf3ac5a1cb0514
- Size of remote file:
- 2.13 GB
- SHA256:
- 008ee4315eb18f77b9fb11da8c1356b9ac36fd6b6284f5b4ee667dad95e0993b
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