Instructions to use Wan-AI/Wan2.2-I2V-A14B-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wan-AI/Wan2.2-I2V-A14B-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("Wan-AI/Wan2.2-I2V-A14B-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") - Inference
- Notebooks
- Google Colab
- Kaggle
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license: apache-2.0
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language:
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- en
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pipeline_tag: image-to-video
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---
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# Wan2.2
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license: apache-2.0
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language:
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- en
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- es
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pipeline_tag: image-to-video
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datasets:
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- nohurry/Opus-4.6-Reasoning-3000x-filtered
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metrics:
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- character
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base_model:
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- Qwen/Qwen3.5-397B-A17B
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- zai-org/GLM-5
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- Qwen/Qwen3.5-397B-A17B-FP8
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- zai-org/GLM-5-FP8
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- bartowski/Qwen_Qwen3.5-397B-A17B-GGUF
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new_version: Qwen/Qwen3.5-397B-A17B
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library_name: adapter-transformers
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tags:
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- art
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---
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# Wan2.2
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