How to use from the
Use from the
Diffusers library
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("radna/LTX-Video-Minimal", 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")

Place this snippet on top of your Inference Code to download the model automatically

from huggingface_hub import snapshot_download

model_path = "..." # The local directory to save downloaded checkpoint
snapshot_download(
    "radna/LTX-Video-Minimal",
    local_dir=model_path,
    local_dir_use_symlinks=False,
    repo_type="model",
)
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