Instructions to use Wan-AI/Wan2.1-T2V-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-T2V-1.3B with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Wan-AI/Wan2.1-T2V-1.3B", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
Download config.json from Wan-AI/Wan2.1-T2V-1.3B: direct link, hf CLI and curl.
- Browser
- Download file 250 Bytes
-
https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/resolve/9790de27e9d6fb42f41a8d21bb5c4706610d6eb1/config.json
- Command line
-
hf download hf://Wan-AI/Wan2.1-T2V-1.3B@9790de27e9d6fb42f41a8d21bb5c4706610d6eb1/config.json
-
curl -L -o config.json https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B/resolve/9790de27e9d6fb42f41a8d21bb5c4706610d6eb1/config.json
250 Bytes
| { | |
| "_class_name": "WanXModel", | |
| "_diffusers_version": "0.30.0", | |
| "dim": 1536, | |
| "eps": 1e-06, | |
| "ffn_dim": 8960, | |
| "freq_dim": 256, | |
| "in_dim": 16, | |
| "model_type": "t2v", | |
| "num_heads": 12, | |
| "num_layers": 30, | |
| "out_dim": 16, | |
| "text_len": 512 | |
| } | |