Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
Flux2KleinPipeline
image-generation
image-editing
flux
Instructions to use rootlocalghost/FLUX.2-klein-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rootlocalghost/FLUX.2-klein-9B 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("rootlocalghost/FLUX.2-klein-9B", 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 rootlocalghost/FLUX.2-klein-9B 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
File size: 446 Bytes
db7d6ed | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"_class_name": "Flux2KleinPipeline",
"_diffusers_version": "0.37.0.dev0",
"is_distilled": true,
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"Qwen3ForCausalLM"
],
"tokenizer": [
"transformers",
"Qwen2TokenizerFast"
],
"transformer": [
"diffusers",
"Flux2Transformer2DModel"
],
"vae": [
"diffusers",
"AutoencoderKLFlux2"
]
}
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