: mainstream Diffusion Transformer (DiT) using a Flow Matching framework.
pipe = WanPipeline.from_pretrained( "Wan-AI/Wan2.1-14B-I2V", torch_dtype=torch.float16 ) video = pipe( image="my_photo.png", prompt="Cinematic dolly zoom into a futuristic city, 8k, high fidelity", num_frames=81 ).video wan2.1 i2v 720p 14b fp16.safetensors
The world of artificial intelligence (AI) is rapidly evolving, with new technologies and models emerging at an unprecedented pace. One such innovation that has garnered significant attention in recent times is the wan2.1 i2v 720p 14b fp16.safetensors model. This article aims to provide an in-depth exploration of this cutting-edge AI model, its capabilities, and the implications it holds for various industries. : mainstream Diffusion Transformer (DiT) using a Flow
– Precision
The model file wan2.1_i2v_720p_14B_fp16.safetensors is a high-fidelity image-to-video (I2V) diffusion model based on the Wan 2.1 architecture. It is designed for generating 720p resolution videos and requires significant hardware resources due to its 14-billion parameter size and FP16 (half-precision) format. Hugging Face Model Specifications Architecture This article aims to provide an in-depth exploration