lightx2v/Minimax-h3-Turbo

Hugging Face Models Trending Models
video-generation image-to-video diffusion huggingface open-weights

Summary

Hugging Face page for the Minimax-h3-Turbo video generation model, with instructions for using it via Diffusers and Colab/Kaggle notebooks.

Task: image-to-video Tags: diffusers, t2v, i2v, r2v, image-to-video, en, zh, base_model:MiniMaxAI/MiniMax-H3, base_model:finetune:MiniMaxAI/MiniMax-H3, license:apache-2.0, region:us
Original Article
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Cached at: 08/07/26, 07:47 PM

lightx2v/Minimax-h3-Turbo · Hugging Face

Source: https://huggingface.co/lightx2v/Minimax-h3-Turbo

Instructions to use lightx2v/Minimax-h3-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • DiffusersHow to use lightx2v/Minimax-h3-Turbo 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("lightx2v/Minimax-h3-Turbo", 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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