Instructions to use Wan-AI/Wan2.2-S2V-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.2-S2V-14B 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("Wan-AI/Wan2.2-S2V-14B", 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
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license: apache-2.0
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pipeline_tag: other
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library_name: diffusers
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---
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# Wan2.2-S2V-14B: Audio-Driven Cinematic Video Generation
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license: apache-2.0
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pipeline_tag: other
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library_name: diffusers
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language:
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- es
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- en
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base_model:
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- deepseek-ai/DeepSeek-V3.1-Base
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- google/gemma-3-270m
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- reedmayhew/claude-3.7-sonnet-reasoning-gemma3-12B
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- yinita/qwen3-8b-v2-gpt5-chat-distill-lora-0814-3epochs
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---
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# Wan2.2-S2V-14B: Audio-Driven Cinematic Video Generation
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