Instructions to use MLL76/FLUX-Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use MLL76/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("MLL76/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
Download epoch_100.pt from MLL76/FLUX-Text: direct link, hf CLI and curl.
- Browser
- Download file 710 MB
-
https://huggingface.co/MLL76/FLUX-Text/resolve/main/epoch_100.pt
- Command line
-
hf download hf://MLL76/FLUX-Text/epoch_100.pt
-
curl -L -o epoch_100.pt https://huggingface.co/MLL76/FLUX-Text/resolve/main/epoch_100.pt
710 MB
- Xet hash:
- a901100ded50198c10348393b1b232ba56854f90f13600585c7d44ced5ed2362
- Size of remote file:
- 710 MB
- SHA256:
- a7e329c97cae19e4fd3ad1b5867036952477dd09e53b90f39b2c68b100060156
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