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 data_text_recog_glyph/LSVT/data-info.json from MLL76/FLUX-Text: direct link, hf CLI and curl.
- Browser
- Download file 20.8 MB
-
https://huggingface.co/MLL76/FLUX-Text/resolve/main/data_text_recog_glyph/LSVT/data-info.json
- Command line
-
hf download hf://MLL76/FLUX-Text/data_text_recog_glyph/LSVT/data-info.json
-
curl -L -o data-info.json https://huggingface.co/MLL76/FLUX-Text/resolve/main/data_text_recog_glyph/LSVT/data-info.json
20.8 MB
- Xet hash:
- 16f50c34c616be0c2c51ccabca0314dc85610e9f79e7e44d50910dce3b14d352
- Size of remote file:
- 20.8 MB
- SHA256:
- 7726b7363dab7fb21115f783d65a8bfe07a8c8b76baa24ec610829206fc51228
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