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
Ref2‑VA + FL2V 4‑step turbo LoRA causes artifacts on fight scenes, request for native Ref2‑4step LoRA
#13
by aronzhan - opened
I'm forcing the combination of minimax_h3_ref2va_int8_convrot model with minimax_h3_fl2v_lightx2v_turbo_4step_v0.1_comfy.safetensors.
It works perfectly for dialogue‑driven narrative videos.
However, fight‑scene outputs suffer from severe artifacts, body distortion and blurring.
When will you release the Ref2‑compatible 4‑step LoRA?