Instructions to use unsloth/FLUX.1-Kontext-dev-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use unsloth/FLUX.1-Kontext-dev-GGUF 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("unsloth/FLUX.1-Kontext-dev-GGUF", 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] - Diffusion Single File
How to use unsloth/FLUX.1-Kontext-dev-GGUF with Diffusion Single File:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle

- Xet hash:
- e8f2ecbbeba9be7d98b6d8c771a9b7c11535aba89f314aff0c3f33f57536ea93
- Size of remote file:
- 596 kB
- SHA256:
- cd8c97b307262eefbbe123d473962057529389b5e56db89030c3f2ad8e521de2
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