Instructions to use AX1Y2JP/LTX2.3-10Eros_split with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AX1Y2JP/LTX2.3-10Eros_split 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("AX1Y2JP/LTX2.3-10Eros_split", 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
metadata
license: other
license_name: ltx-2-community-license-agreement
license_link: https://github.com/Lightricks/LTX-2/blob/main/LICENSE
base_model:
- TenStrip/LTX2.3-10Eros
base_model_relation: quantized
tags:
- image-to-video
- ltx-2-3
- ltx-video
- sulphur-2
- 10Eros
- comfyui
library_name: diffusers
inference: false
Separated LTX2.3-10Eros checkpoint for alternative way to load the models in Comfy