Instructions to use LHRS/RSSR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LHRS/RSSR with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LHRS/RSSR", 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:
- fab05fd1f7be7e53610da6adcdcd4661d0b11ab1f385f5e70a104d4241e59fa8
- Size of remote file:
- 4.31 GB
- SHA256:
- 1e60a8cfda452a24e7bfa72e15695b8a6aac9c070921430d6b91208d4ea54148
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