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
ref2v lora blurs the hands and the overall quality is bad.
This lora messes the hands, they become blurry. its bad, the normal fl2v lightx2v didn't do this in a ref2v workflow. just swapping it in - same settings and this specific ref2v lora is bad. the quality is terrible for the overall ref2v video output. Maybe i am doing something wrong? but same settings work fine for the fl2v lightx2v lora in a ref2v workflow.
"blurs" hands for me as well, really just bad rendering of hands.
I think the best version is minimax_h3_fl2v_lightx2v_turbo_4step_v0.1_comfy.safetensors by Kijai. I use this for both fl2V and red2V. It's the most detailed in my opinion. All other versions seems blurry specially when there's a fast motion in the scene.
I think the best version is minimax_h3_fl2v_lightx2v_turbo_4step_v0.1_comfy.safetensors by Kijai. I use this for both fl2V and red2V. It's the most detailed in my opinion. All other versions seems blurry specially when there's a fast motion in the scene.
You are right. That's the one I use. That's the best one.
I found it better with er_sde and beta.
I had no idea the fl2V model works in the ref2V workflow. I tried it with the turbo LoRa, results look much clearer.