Instructions to use Runware/Flex-Redux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Runware/Flex-Redux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Runware/Flex-Redux", 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
- Xet hash:
- 8cc17ff12e4c69fab36d83cb258a87db2fdf337337a7243b0b4a29be46c398b0
- Size of remote file:
- 858 MB
- SHA256:
- dc315325a08b9ada2eb1f2cf9fb1b6874defacf1f3b0ae8dc21bf021d6437db1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.