WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory
Paper • 2609.24984 • Published • 113
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/WorldCrafter-Base", 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")WorldCrafter-Base
Base transformer weights and their matching camera adapter and LoRA for the WorldCrafter inference code.
Place this directory beside WorldCrafter-Fast. Base reads the following shared folders from Fast: repencoder/, text_encoder/, tokenizer/, vae/, and scheduler/. Base does not need Fast's transformer or adapter folders. The relative path is configured in inference_config.json.
From the code repository root:
python inference.py --model-type base --model-path weights/WorldCrafter-Base --output-path outputs/base.mp4
Keep the Base-specific transformer/ and adapter/ together. SHA256SUMS covers the packaged Base files; shared component hashes are recorded in Fast's package.
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