Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
Flux2KleinPipeline
text-to-image
image-editing
flux
Instructions to use YuCollection/FLUX.2-klein-4B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use YuCollection/FLUX.2-klein-4B-Diffusers 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("YuCollection/FLUX.2-klein-4B-Diffusers", 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 YuCollection/FLUX.2-klein-4B-Diffusers 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 model_index.json with huggingface_hub
Browse files- model_index.json +25 -0
model_index.json
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{
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"_class_name": "Flux2KleinPipeline",
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"_diffusers_version": "0.37.0.dev0",
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"is_distilled": true,
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"scheduler": [
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"diffusers",
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"FlowMatchEulerDiscreteScheduler"
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],
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"text_encoder": [
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"transformers",
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"Qwen3ForCausalLM"
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],
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"tokenizer": [
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"transformers",
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"Qwen2TokenizerFast"
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],
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"transformer": [
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"diffusers",
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"Flux2Transformer2DModel"
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],
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"vae": [
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"diffusers",
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"AutoencoderKLFlux2"
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]
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}
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