Instructions to use CaaretAI/FLUX.1-dev-FP8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CaaretAI/FLUX.1-dev-FP8 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CaaretAI/FLUX.1-dev-FP8", 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 CaaretAI/FLUX.1-dev-FP8: direct link, hf CLI and curl.
- Browser
- Download file 168 MB
-
https://huggingface.co/CaaretAI/FLUX.1-dev-FP8/resolve/main/vae/diffusion_pytorch_model.bin
- Command line
-
hf download hf://CaaretAI/FLUX.1-dev-FP8/vae/diffusion_pytorch_model.bin
-
curl -L -o diffusion_pytorch_model.bin https://huggingface.co/CaaretAI/FLUX.1-dev-FP8/resolve/main/vae/diffusion_pytorch_model.bin
168 MB
- Xet hash:
- 7316c975c46e939567cb66e32a38a020ad2de21c9c09ee79751e58ccd0bd5bb5
- Size of remote file:
- 168 MB
- SHA256:
- 71626130e357339cfff205609e41df5576b10274702aebed2e00656192b1c61a
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