Instructions to use Muapi/fertilization-concept with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Muapi/fertilization-concept with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cocktailpeanut/pony-diffusion-v6-xl", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Muapi/fertilization-concept") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 1f0ffa8feceaf41da34efc87c2988a6dcdb65fe572f6eae237b80dc1b1db465e
- Size of remote file:
- 229 MB
- SHA256:
- c5f87236eb9ca90ee16b9aef163900cc03e72e3b83db32648e6651e55965baae
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