Instructions to use lightx2v/Minimax-h3-Turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How 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
V0.1 is a preview version
v0.1 is only a preview release. You can refer to the videos below for examples of its current performance. We will improve its quality over the next few days and release an updated version
Thanks !
Thank you Lightx2v team!
what are the various recommended settings?
Thank you for good lora - like it!
But I have a question - do you have any plan to make 8 steps light lora to get better result with dynamic movement scenes?
@StefanFalkok
of course we will.
The todo list is: 1, improve fl2v 4 step , 2, train fl2v 8 step & ref2v 4 step
How many steps to use with this Lora?
Thanks.
@StefanFalkok
of course we will.The todo list is: 1, improve fl2v 4 step , 2, train fl2v 8 step & ref2v 4 step
Also, should we wait turbo loras with I2V and First-Last Frame 2V, or will it be the one turbo universal lora for t2v, i2v for fl2va model?
@StefanFalkok
of course we will.The todo list is: 1, improve fl2v 4 step , 2, train fl2v 8 step & ref2v 4 step
Also, should we wait turbo loras with I2V and First-Last Frame 2V, or will it be the one turbo universal lora for t2v, i2v for fl2va model?
same question
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