Instructions to use diffusers-internal-dev/chronoedit-modular with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use diffusers-internal-dev/chronoedit-modular with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("diffusers-internal-dev/chronoedit-modular", 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
Download upload_block.py from diffusers-internal-dev/chronoedit-modular: direct link, hf CLI and curl.
- Browser
- Download file 348 Bytes
-
https://huggingface.co/diffusers-internal-dev/chronoedit-modular/resolve/main/upload_block.py
- Command line
-
hf download hf://diffusers-internal-dev/chronoedit-modular/upload_block.py
-
curl -L -o upload_block.py https://huggingface.co/diffusers-internal-dev/chronoedit-modular/resolve/main/upload_block.py
348 Bytes
| from diffusers.modular_pipelines import WanModularPipeline | |
| from modular_blocks import ChronoEditBlocks | |
| repo_id = "nvidia/ChronoEdit-14B-Diffusers" | |
| blocks = ChronoEditBlocks() | |
| blocks.push_to_hub("diffusers-internal-dev/chronoedit-modular") | |
| pipe = WanModularPipeline(blocks, repo_id) | |
| pipe.push_to_hub("diffusers-internal-dev/chronoedit-modular") | |