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8 Artefaktediffusion_pytorch_model-00001-of-00006.safetensors
safetensors · 9,21 GB · SHA-256 569d54a07279…0078 · Hugging Face
Herunterladendiffusion_pytorch_model-00002-of-00006.safetensors
safetensors · 9,16 GB · SHA-256 b17ff172f262…0e46 · Hugging Face
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2 Auszügediffusion_pytorch_model-00003-of-00006.safetensors
safetensors · 9,16 GB · SHA-256 741fd1508cd0…2cea · Hugging Face
Herunterladendiffusion_pytorch_model-00004-of-00006.safetensors
safetensors · 9,16 GB · SHA-256 47b08ba289b1…81ba · Hugging Face
Herunterladendiffusion_pytorch_model-00005-of-00006.safetensors
safetensors · 9,16 GB · SHA-256 29e35f4cf0e3…ee88 · Hugging Face
Herunterladendiffusion_pytorch_model-00006-of-00006.safetensors
safetensors · 7,37 GB · SHA-256 91ac087a40b8…c146 · Hugging Face
Herunterladenmodels_t5_umt5-xxl-enc-bf16.pth
pth · 10,6 GB · SHA-256 7cace0da2b44…d81d · Hugging Face
Herunterladen--- license: apache-2.0 language: - en - zh pipeline_tag: text-to-video tags: - video generation library_name: diffusers inference: parameters: num_inference_steps: 10 --- # Wan2.1 <p align="center"> <img src="assets/logo.png" width="400"/> <p> <p align="center"> 💜 <a href=""><b>Wan</b></a>    |    🖥️ <a href="https://github.com/Wan-Video/Wan2.1">GitHub</a>    |   🤗 <a href="https://huggingface.co/Wan-AI/">Hugging Face</a>   |   🤖 <a href="https://modelscope.cn/organization/Wan-AI">ModelScope</a>   |    📑 <a href="">Paper (Coming soon)</a>    |    📑 <a href="https://wanxai.com">Blog</a>    |   💬 <a href="https://gw.alicdn.com/imgextra/i2/O1CN01tqjWFi1ByuyehkTSB_!!6000000000015-0-tps-611-1279.jpg">WeChat Group</a>   |    📖 <a href="https://discord.gg/p5XbdQV7">Discord</a>   <br> ----- [**Wan: Open and Advanced Large-Scale Video Generative Models**]("") <be> In this repository, we present **Wan2.1**, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. **Wan2.1** offers these key features: - 👍 **SOTA Performance**: **Wan2.1** consistently outperforms existing open-source models and state-of-the-art commercial solutions across multiple benchmarks. - 👍 **Supports Consumer-grade GPUs**: The T2V-1.3B model requires only 8.19 GB VRAM, making it compatible with almost all consumer-grade GPUs. It can generate a 5-second 480P video on an RTX 4090 in about 4 minutes (without optimization techniques like quantization). Its performance is even comparable to some closed-source models. - 👍 **Multiple Tasks**: **Wan2.1** excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation. - 👍 **Visual Text Generation**: **Wan2.1** is the first video model capable of generating both Chinese and English text, featuring robust text generation that enhances its practical applications. - 👍 **Powerful Video VAE**: **Wan-VAE** delivers exceptional efficiency and performance, encoding and decoding 1080P videos of any length while preserving temporal information, making it an ideal foundation for video and image generation. This repository features our T2V-14B model, which establishes a new SOTA performance benchmark among bo...
Source context: 8 downloads · 0 likes · Pipeline text-to-video · Library diffusers · Repo Bear650/Wan2.1-T2V-14B