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Wan 2.2 T2V A14B Diffusers Reduced To 2layers

💜 Wan | 🖥️ GitHub | 🤗 Hugging Face | 🤖 ModelScope | 📑 Technical Report | 📑 Blog | 💬 WeChat Group | 📖 Discord

TipoOtherVersiónRevision 0316937Ccalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
484 MB–3,49 GB
Versión
vRevision 0316937
Actualizado
27 sept 2026
Descargas
2
Fuente
Hugging Face

Extracto de la fuente

💜 Wan | 🖥️ GitHub | 🤗 Hugging Face | 🤖 ModelScope | 📑 Technical Report | 📑 Blog | 💬 WeChat Group | 📖 Discord

Fuentes

1 fuente
Hugging FacePrincipalVersión 0316937469c047bee3331b30d7b660a84e3d72e6
huggingface.co/xuechendi/Wan2.2-T2V-A14B-Diffusers-reduced-to-2layers/tree/0316937469c047bee3331b30d7b660a84e3d72e6

Verificado 30 ago

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Artefactos del modelo

4 artefactos

text_encoder/model.safetensors

safetensors · 2,67 GB · SHA-256 5e541a653557…538b · Hugging Face

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transformer_2/diffusion_pytorch_model.safetensors

safetensors · 3,49 GB · SHA-256 6b2a2febb8b5…44b1 · Hugging Face

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transformer/diffusion_pytorch_model.safetensors

safetensors · 3,49 GB · SHA-256 e55c1e4fbce6…cd23 · Hugging Face

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vae/diffusion_pytorch_model.safetensors

safetensors · 484 MB · SHA-256 d6e524b3fffe…e793 · Hugging Face

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Extractos de fuentes

2 extractos

--- license: apache-2.0 pipeline_tag: text-to-video --- # Wan2.2 <p align="center"> <img src="assets/logo.png" width="400"/> <p> <p align="center"> 💜 <a href="https://wan.video"><b>Wan</b></a> &nbsp&nbsp | &nbsp&nbsp 🖥️ <a href="https://github.com/Wan-Video/Wan2.2">GitHub</a> &nbsp&nbsp | &nbsp&nbsp🤗 <a href="https://huggingface.co/Wan-AI/">Hugging Face</a>&nbsp&nbsp | &nbsp&nbsp🤖 <a href="https://modelscope.cn/organization/Wan-AI">ModelScope</a>&nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://arxiv.org/abs/2503.20314">Technical Report</a> &nbsp&nbsp | &nbsp&nbsp 📑 <a href="https://wan.video/welcome?spm=a2ty_o02.30011076.0.0.6c9ee41eCcluqg">Blog</a> &nbsp&nbsp | &nbsp&nbsp💬 <a href="https://gw.alicdn.com/imgextra/i2/O1CN01tqjWFi1ByuyehkTSB_!!6000000000015-0-tps-611-1279.jpg">WeChat Group</a>&nbsp&nbsp | &nbsp&nbsp 📖 <a href="https://discord.gg/AKNgpMK4Yj">Discord</a>&nbsp&nbsp <br> ----- [**Wan: Open and Advanced Large-Scale Video Generative Models**](https://arxiv.org/abs/2503.20314) <be> We are excited to introduce **Wan2.2**, a major upgrade to our foundational video models. With **Wan2.2**, we have focused on incorporating the following innovations: - 👍 **Effective MoE Architecture**: Wan2.2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. By separating the denoising process cross timesteps with specialized powerful expert models, this enlarges the overall model capacity while maintaining the same computational cost. - 👍 **Cinematic-level Aesthetics**: Wan2.2 incorporates meticulously curated aesthetic data, complete with detailed labels for lighting, composition, contrast, color tone, and more. This allows for more precise and controllable cinematic style generation, facilitating the creation of videos with customizable aesthetic preferences. - 👍 **Complex Motion Generation**: Compared to Wan2.1, Wan2.2 is trained on a significantly larger data, with +65.6% more images and +83.2% more videos. This expansion notably enhances the model's generalization across multiple dimensions such as motions, semantics, and aesthetics, achieving TOP performance among all open-sourced and closed-sourced models. - 👍 **Efficient High-Definition Hybrid TI2V**: Wan2.2 open-sources a 5B model built with our advanced Wan2.2-VAE that achieves a compression ratio of **16×16×4**. This model supports both text-to-video and image-...

Source context: 2 downloads · 0 likes · Pipeline text-to-video · Library diffusers · Repo xuechendi/Wan2.2-T2V-A14B-Diffusers-reduced-to-2layers