Instructions to use SimonJonsson1999/test_lora_decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use SimonJonsson1999/test_lora_decoder with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("kandinsky-community/kandinsky-2-2-decoder", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("SimonJonsson1999/test_lora_decoder") 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:
- 79b1638518eca65a47619c39d951914ca358588db7dd14cd9f0d37d55e8b93dd
- Size of remote file:
- 3.31 MB
- SHA256:
- fa221d794d4ea8bb770c1c7ad34ceae714c06208371dfe87040ebd0926efae5b
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