Image-to-Video
Diffusers
Safetensors
English
video-generation
diffusion
4d-control
camera-control
object-motion
world-model
Instructions to use TencentARC/VerseCrafter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TencentARC/VerseCrafter with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image, export_to_video # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TencentARC/VerseCrafter", dtype=torch.bfloat16, device_map="cuda") pipe.to("cuda") prompt = "A man with short gray hair plays a red electric guitar." image = load_image( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/guitar-man.png" ) output = pipe(image=image, prompt=prompt).frames[0] export_to_video(output, "output.mp4") - Notebooks
- Google Colab
- Kaggle
File size: 760 Bytes
1a3115c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 | {
"_class_name": "VerseCrafterWanTransformer3DModel",
"_diffusers_version": "0.30.1",
"add_control_adapter": false,
"add_ref_conv": false,
"cross_attn_norm": true,
"cross_attn_type": null,
"dim": 5120,
"downscale_factor_control_adapter": 8,
"eps": 1e-06,
"ffn_dim": 13824,
"freq_dim": 256,
"hidden_size": 2048,
"in_channels": 16,
"in_dim": 16,
"in_dim_control_adapter": 24,
"in_dim_ref_conv": 16,
"model_type": "t2v",
"num_heads": 40,
"num_layers": 40,
"out_dim": 16,
"patch_size": [
1,
2,
2
],
"qk_norm": true,
"text_dim": 4096,
"text_len": 512,
"geoada_in_dim": 128,
"geoada_layers": [
0,
5,
10,
15,
20,
25,
30,
35
],
"window_size": [
-1,
-1
]
}
|