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
Ctrl+K
- scheduler
- text_encoder
- text_encoder_2
- tokenizer
- tokenizer_2
- unet
- 1.61 kB
- 14.1 kB
- 288 MB xet
- 170 MB xet
- 609 Bytes
- 4.31 GB xet
- 4.31 GB xet
- 4.3 GB xet
- 4.3 GB xet
- 4.3 GB xet
- 4.28 GB xet
- 4.3 GB xet
- 4.3 GB xet
- 1.94 GB xet
- 4.31 GB xet
- 4.31 GB xet
- 4.31 GB xet
- 4.31 GB xet
- 4.31 GB xet
- 4.31 GB xet
- 4.31 GB xet
- 4.31 GB xet