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
- Draw Things
- DiffusionBee
- Xet hash:
- 34f236297ec9f0df1a7ba548c7ba9a6a54670a979366539ceb97f62486411331
- Size of remote file:
- 3.44 GB
- SHA256:
- e67a533bdaac6aa4293951bdcb1e44cb83f784975a8fdf49872a8fcd4842552e
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