Instructions to use wavespeed/FLUX.1-dev-e4m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use wavespeed/FLUX.1-dev-e4m3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("wavespeed/FLUX.1-dev-e4m3", 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:
- ab373ba20777ef01ae7e4c70fba12197dd53e874f20c719f2398ca77688f09c7
- Size of remote file:
- 246 MB
- SHA256:
- f68b6f4676717828773f47aeaea857788fb586789706748f5ef8f89ac5ec2bd1
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