Image-to-Image
Diffusers
Safetensors
MLX
QwenImageEditPlusPipeline
style-transfer
image-editing
qwen-image-edit
Instructions to use mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16 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("mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16", 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] - MLX
How to use mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir TeleStyleV2-Qwen-Image-Edit-2511-bf16 mlx-community/TeleStyleV2-Qwen-Image-Edit-2511-bf16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Xet hash:
- 4bd2f092eeec244c0448f13e31edd4b25e625568713e4155993a3dea90c7437a
- Size of remote file:
- 11.4 MB
- SHA256:
- 9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
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