Image-to-Video
Diffusers
Safetensors
English
Chinese
WanGameActionImageToVideoPipeline
video
video-generation
Instructions to use weizhou03/Wan2.1-Game-Fun-1.3B-InP-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use weizhou03/Wan2.1-Game-Fun-1.3B-InP-Diffusers 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("weizhou03/Wan2.1-Game-Fun-1.3B-InP-Diffusers", 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: 587 Bytes
b5f4084 1442946 b5f4084 f2c48e7 b5f4084 | 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": "WanGameActionImageToVideoPipeline",
"_diffusers_version": "0.33.0.dev0",
"image_encoder": [
"transformers",
"CLIPVisionModelWithProjection"
],
"image_processor": [
"transformers",
"CLIPImageProcessor"
],
"scheduler": [
"diffusers",
"UniPCMultistepScheduler"
],
"text_encoder": [
"transformers",
"UMT5EncoderModel"
],
"tokenizer": [
"transformers",
"T5TokenizerFast"
],
"transformer": [
"diffusers",
"WanGameActionTransformer3DModel"
],
"vae": [
"diffusers",
"AutoencoderKLWan"
]
}
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