Image-to-Image
Diffusers
Safetensors
Diffusion Single File
English
Flux2KleinPipeline
image-generation
image-editing
flux
Instructions to use internlm/ETCHR-FLUX.2-klein-9B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use internlm/ETCHR-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("internlm/ETCHR-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 internlm/ETCHR-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
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@@ -102,6 +102,12 @@ Our work is based on [FLUX.2-klein-base-9B](https://huggingface.co/black-forest-
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## ✒️Citation
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If you find this project useful, please kindly cite:
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```
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## ❤️ Acknowledgement
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The base model is [FLUX.2-klein-base-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9B), a powerful image-to-image model.
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## ✒️Citation
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If you find this project useful, please kindly cite:
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@article{zhang2026etchr,
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title={ETCHR: Editing To Clarify and Harness Reasoning},
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author={Beichen Zhang, Yuhong Liu, Jinsong Li, Yuhang Zang, Jiaqi Wang, Dahua Lin},
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journal={arXiv preprint arXiv:2605.23897},
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year={2026}
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}
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```
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## ❤️ Acknowledgement
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The base model is [FLUX.2-klein-base-9B](https://huggingface.co/black-forest-labs/FLUX.2-klein-base-9B), a powerful image-to-image model.
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