Instructions to use nvidia/ChronoEdit-14B-Diffusers-Upscaler-Lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nvidia/ChronoEdit-14B-Diffusers-Upscaler-Lora 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("nvidia/ChronoEdit-14B-Diffusers", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("nvidia/ChronoEdit-14B-Diffusers-Upscaler-Lora") 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] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- Xet hash:
- 6cbce892c0e05b2542b6e73666a74ee7a7c04aa9333088f3177fc8e8a8a76b20
- Size of remote file:
- 307 MB
- SHA256:
- 7b7f47060eb40cc25330ea32c0560f7c87366699e1fe27ce215c026389779eca
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