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 Settings
- Draw Things
- DiffusionBee
Download vae/diffusion_pytorch_model.bin from wavespeed/FLUX.1-dev-e4m3: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/wavespeed/FLUX.1-dev-e4m3/resolve/7a446aeee7bb4b397d4e95cc8dcb2bf420203dfa/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://wavespeed/FLUX.1-dev-e4m3@7a446aeee7bb4b397d4e95cc8dcb2bf420203dfa/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/wavespeed/FLUX.1-dev-e4m3/resolve/7a446aeee7bb4b397d4e95cc8dcb2bf420203dfa/vae/diffusion_pytorch_model.bin
168 MB
- Xet hash:
- 040ca8a6dd8707fb9e8df46ce88d5351a9a46f9db40e70c9f0d4947417dffa32
- Size of remote file:
- 168 MB
- SHA256:
- 440feb56622cd4db6127ce887ae4f9ada909e0813e19d9bd04a7638d56bbf3be
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