Instructions to use GamerC0der/MiniDiffusion1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GamerC0der/MiniDiffusion1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("GamerC0der/MiniDiffusion1") prompt = "Dog, Realistic, 4k, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d11e73460c2eafe175e82ed052835855e77025ba4af900eba9d7a7a5193d1c3f
- Size of remote file:
- 75.6 MB
- SHA256:
- dc3a25164c85b499a55a5c27980bbf3af3c8dc9ece90bd8d035c3226ffdc3a4c
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