Image-to-Image
Diffusers
Safetensors
English
Chinese
WanImageToVideoPipeline
image editing
video generation
Instructions to use NopenAI/nv-chronoedit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use NopenAI/nv-chronoedit 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("NopenAI/nv-chronoedit", 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] - Notebooks
- Google Colab
- Kaggle
File size: 461 Bytes
5265bb2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | {
"_class_name": "WanTransformer3DModel",
"_diffusers_version": "0.33.1",
"added_kv_proj_dim": 5120,
"attention_head_dim": 128,
"cross_attn_norm": true,
"eps": 1e-06,
"ffn_dim": 13824,
"freq_dim": 256,
"image_dim": 1280,
"in_channels": 36,
"num_attention_heads": 40,
"num_layers": 40,
"out_channels": 16,
"patch_size": [
1,
2,
2
],
"qk_norm": "rms_norm_across_heads",
"rope_max_seq_len": 1024,
"text_dim": 4096
}
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