Instructions to use DaveLoay/Riffusion_FineTuning_Tutorial with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DaveLoay/Riffusion_FineTuning_Tutorial with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DaveLoay/Riffusion_FineTuning_Tutorial", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- a0051d580eab485ff112b2ed2118c6d09772319708acee60ab2941dba78c9331
- Size of remote file:
- 6.88 GB
- SHA256:
- e64081e64a0b63f6dc2293b063eb83d1a53cf71d4182ec8c18b35355a38cf2e3
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