Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
Flux2KleinPipeline
text-to-image
image-editing
flux
Instructions to use xcreates/FLUX.2-klein-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use xcreates/FLUX.2-klein-4B 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("xcreates/FLUX.2-klein-4B", 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 xcreates/FLUX.2-klein-4B 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
Upload complete model
Browse files
README.md
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**See FLUX.2-klein-4B in action - [demonstration video
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## Usage Notes
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#### Tested using [xCreate app v1.1.1](https://xcreate.com)
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##### For more details see [demonstration video
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## Disclaimer
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- flux
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**See FLUX.2-klein-4B in action - [demonstration video](https://youtu.be/K6DiPiDgDds)**
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## Usage Notes
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#### Tested using [xCreate app v1.1.1](https://xcreate.com)
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* M3 Ultra: ~9.7 seconds for a generation
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* M4 Max: ~17.8 seconds for a generation
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* M1 Max: ~56 seconds for a generation
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* Memory usage: ~28 GB
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##### For more details see [demonstration video](https://youtu.be/K6DiPiDgDds) or visit [black-forest-labs/FLUX.2-klein-4B](https://huggingface.co/black-forest-labs/FLUX.2-klein-4B).
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## Disclaimer
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