Instructions to use weizhou03/Wan2.1-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-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-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: 582 Bytes
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"_name_or_path": "laion/CLIP-ViT-H-14-laion2B-s32B-b79K",
"architectures": [
"CLIPVisionModelWithProjection"
],
"attention_dropout": 0.0,
"dropout": 0.0,
"hidden_act": "gelu",
"hidden_size": 1280,
"image_size": 224,
"initializer_factor": 1.0,
"initializer_range": 0.02,
"intermediate_size": 5120,
"layer_norm_eps": 1e-05,
"model_type": "clip_vision_model",
"num_attention_heads": 16,
"num_channels": 3,
"num_hidden_layers": 32,
"patch_size": 14,
"projection_dim": 1024,
"torch_dtype": "float32",
"transformers_version": "4.48.0.dev0"
}
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