Instructions to use TencentARC/WorldCrafter-Fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TencentARC/WorldCrafter-Fast 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/WorldCrafter-Fast", 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: 1,753 Bytes
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"_class_name": "WorldCrafter",
"_module": "worldcrafter",
"_format": "worldcrafter_fast_model_index_v1",
"_diffusers_version": "0.37.0",
"_loading": {
"entrypoint": "worldcrafter.WorldCrafter.from_pretrained",
"model_type": "fast",
"requires_custom_loader": true,
"inference_config": "inference_config.json",
"manifest": "manifest.json"
},
"_pipeline": {
"library": "worldcrafter",
"class_name": "WorldCrafterPipeline",
"is_distilled": true
},
"transformer_high_noise": [
"worldcrafter",
"WorldCrafterTransformer3DModel"
],
"transformer_low_noise": [
"worldcrafter",
"WorldCrafterTransformer3DModel"
],
"repencoder": [
"worldcrafter",
"RepEncoder"
],
"text_encoder": [
"transformers",
"UMT5EncoderModel"
],
"tokenizer": [
"transformers",
"T5TokenizerFast"
],
"vae": [
"diffusers",
"AutoencoderKLWan"
],
"scheduler": [
"worldcrafter",
"WorldCrafterScheduler"
],
"_adapters": {
"high_noise": {
"transformer": "transformer_high_noise",
"lora_weights": "adapter_high_noise/pytorch_lora_weights.safetensors",
"camera_weights": "adapter_high_noise/transformer_partial.pth",
"timestep_contract": "adapter_high_noise/dmd_timestep_contract.json",
"repencoder_reference": "adapter_high_noise/repencoder_frozen.json"
},
"low_noise": {
"transformer": "transformer_low_noise",
"lora_weights": "adapter_low_noise/pytorch_lora_weights.safetensors",
"camera_weights": "adapter_low_noise/transformer_partial.pth",
"timestep_contract": "adapter_low_noise/dmd_timestep_contract.json",
"repencoder_reference": "adapter_low_noise/repencoder_frozen.json"
}
}
}
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