Image-to-Video
Diffusers
Safetensors
English
LTX2Pipeline
text-to-video
ltx-2
ltx-2-3
ltx-video
lightricks
Instructions to use CalamitousFelicitousness/LTX-2.3-dev-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use CalamitousFelicitousness/LTX-2.3-dev-Diffusers 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("CalamitousFelicitousness/LTX-2.3-dev-Diffusers", 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
File size: 570 Bytes
c80cbdc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | {
"do_convert_rgb": null,
"do_normalize": true,
"do_pan_and_scan": null,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "Gemma3ImageProcessor",
"image_seq_length": 256,
"image_std": [
0.5,
0.5,
0.5
],
"pan_and_scan_max_num_crops": null,
"pan_and_scan_min_crop_size": null,
"pan_and_scan_min_ratio_to_activate": null,
"processor_class": "Gemma3Processor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 896,
"width": 896
}
}
|