Instructions to use JD97/Riffusion_sentiment_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JD97/Riffusion_sentiment_LoRA with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JD97/Riffusion_sentiment_LoRA", 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:
- 8dcc8ecdf3d635d67c6ef268475ea0e5ea797700f85dd14cb2223119cce19a41
- Size of remote file:
- 521 Bytes
- SHA256:
- 4a7bf3e47852bb01bb3f0271ee593b01c04529ee3ea7f32f8031072943be0d4e
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