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:
- 7d0c6f0ad4f14ec0d7c53be585cae88184aadab2c08c59661fac089039fefa21
- Size of remote file:
- 4.85 GB
- SHA256:
- e03175a316fa025f967c84c952392088730e7f7c2369303fee961bc8cbed46a3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.