Instructions to use Jaytsh/FLUX-Enhance1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jaytsh/FLUX-Enhance1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jaytsh/FLUX-Enhance1") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- 14b016d31b217fbc4a2f6d7b95d6571c2fe5da58e802fc907e1fde693be8562d
- Size of remote file:
- 166 MB
- SHA256:
- 20f96c13edd4478b2d14adcc46936dff746734d652d3775c607a409eb37d7330
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