Instructions to use Wan-AI/Wan2.1-T2V-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.1-T2V-14B 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-14B", 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
model_index.json
#36
by shreyas231219 - opened
No description provided.
{
"_class_name": "TextToVideoSDPipeline",
"_diffusers_version": "0.25.0",
"scheduler": ["diffusers", "DDIMScheduler"],
"text_encoder": ["transformers", "CLIPTextModel"],
"tokenizer": ["transformers", "CLIPTokenizer"],
"unet": ["diffusers", "UNet2DConditionModel"],
"vae": ["diffusers", "AutoencoderKL"]
}
this is the code for the model_index.json
shreyas231219 changed pull request status to open