Instructions to use BxuanZ/FLUX-RS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BxuanZ/FLUX-RS with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BxuanZ/FLUX-RS", 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
Add link to paper, code and citation
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the Hugging Face community team.
This PR improves the model card by:
- Adding a clear link to the associated research paper: SHARP: Spectrum-aware Highly-dynamic Adaptation for Resolution Promotion in Remote Sensing Synthesis.
- Adding a link to the official GitHub repository for the SHARP framework.
- Including a BibTeX citation section for easier referencing in research work.
The metadata and usage snippets are preserved as they are already accurate and functional.