Instructions to use nvidia/ChronoEdit-14B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nvidia/ChronoEdit-14B-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("nvidia/ChronoEdit-14B-Diffusers", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b804c0192355a0fdd14e805bb3453cc98f904cf85a008ef22c84fa9a48dd3b71
- Size of remote file:
- 4.85 GB
- SHA256:
- 1d549d76eb41f9823aec08af284a58495cf8915dcec2bb8449c6163fb0aac974
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.