Instructions to use John6666/hyper-flux1-dev-fp8-flux with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use John6666/hyper-flux1-dev-fp8-flux with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("John6666/hyper-flux1-dev-fp8-flux", 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
Original model is here. This model created by bdsqlsz. Hyper FLUX.1-dev-related LoRAs are here.
Notice
This is an experimental conversion in Spaces using a homebrew script. serverless Inference API does not currently support torch float8_e4m3fn, so it does not work. I have not been able to confirm if the conversion is working properly. Please consider this as a test run only.
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