Instructions to use TencentARC/WorldCrafter-Base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TencentARC/WorldCrafter-Base 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-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") - Notebooks
- Google Colab
- Kaggle
File size: 665 Bytes
11cc7fa | 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 | {
"_class_name": "WorldCrafterTransformer3DModel",
"_diffusers_version": "0.38.0.dev0",
"added_kv_proj_dim": null,
"attention_head_dim": 128,
"cross_attn_norm": true,
"eps": 1e-06,
"ffn_dim": 13824,
"freq_dim": 256,
"guidance_cross_attn": true,
"has_multi_term_memory_patch": true,
"history_scale_mode": "per_head",
"in_channels": 16,
"is_amplify_history": false,
"num_attention_heads": 40,
"num_layers": 40,
"out_channels": 16,
"patch_size": [
1,
2,
2
],
"qk_norm": "rms_norm_across_heads",
"rope_dim": [
44,
42,
42
],
"rope_theta": 10000.0,
"text_dim": 4096,
"zero_history_timestep": true
}
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