Image-to-Video
Diffusers
Safetensors
LTX2Pipeline
text-to-video
video-to-video
image-text-to-video
audio-to-video
text-to-audio
video-to-audio
audio-to-audio
text-to-audio-video
image-to-audio-video
image-text-to-audio-video
ltx-2
ltx-video
ltxv
lightricks
Instructions to use Lightricks/LTX-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Lightricks/LTX-2 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("Lightricks/LTX-2", 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") - Inference
- Notebooks
- Google Colab
- Kaggle
| { | |
| "_class_name": "LTX2Vocoder", | |
| "_diffusers_version": "0.37.0.dev0", | |
| "hidden_channels": 1024, | |
| "in_channels": 128, | |
| "leaky_relu_negative_slope": 0.1, | |
| "out_channels": 2, | |
| "output_sampling_rate": 24000, | |
| "resnet_dilations": [ | |
| [ | |
| 1, | |
| 3, | |
| 5 | |
| ], | |
| [ | |
| 1, | |
| 3, | |
| 5 | |
| ], | |
| [ | |
| 1, | |
| 3, | |
| 5 | |
| ] | |
| ], | |
| "resnet_kernel_sizes": [ | |
| 3, | |
| 7, | |
| 11 | |
| ], | |
| "upsample_factors": [ | |
| 6, | |
| 5, | |
| 2, | |
| 2, | |
| 2 | |
| ], | |
| "upsample_kernel_sizes": [ | |
| 16, | |
| 15, | |
| 8, | |
| 4, | |
| 4 | |
| ] | |
| } | |