Instructions to use diffusers-internal-dev/flux2-bnb-4bit-modular with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/flux2-bnb-4bit-modular 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("diffusers-internal-dev/flux2-bnb-4bit-modular", 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
| language: | |
| - en | |
| license: other | |
| license_name: flux-dev-non-commercial-license | |
| license_link: https://huggingface.co/black-forest-labs/FLUX.2-dev/blob/main/LICENSE.txt | |
| extra_gated_prompt: >- | |
| By clicking "Agree", you agree to the [FLUX [dev] Non-Commercial License | |
| Agreement](https://huggingface.co/black-forest-labs/FLUX.2-dev/blob/main/LICENSE.txt) | |
| and acknowledge the [Acceptable Use | |
| Policy](https://bfl.ai/legal/usage-policy). | |
| tags: | |
| - image-generation | |
| - image-editing | |
| - flux.2 | |
| pipeline_tag: image-to-image | |
| library_name: diffusers | |
| This repository contains the NF4 quantized DiT and the text encoders from https://huggingface.co/black-forest-labs/FLUX.2-dev. The VAE | |
| is not quantized. | |
| Refer to [this blog post](https://huggingface.co/blog/flux-2) to learn more. |