Instructions to use GD-ML/FLUX-Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use GD-ML/FLUX-Text with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("GD-ML/FLUX-Text", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- bb885c6930562bcbf4a5b56075405346255aeddd3715be3e678d3ff1fa2d6a24
- Size of remote file:
- 1.16 MB
- SHA256:
- 06cf65d0f55764f5dcb5b017738f8c4bb7c83cdb4f1a0fca8ea1091c5123f83f
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