Instructions to use chfm/Ltx2.3-VBVR-lora-I2V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use chfm/Ltx2.3-VBVR-lora-I2V with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Lightricks/LTX-2.3", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("chfm/Ltx2.3-VBVR-lora-I2V") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- Xet hash:
- 67e951f7e23b988278993b7aafa9e7685904b10a8a22dd671d3ba8d7175f32c2
- Size of remote file:
- 554 MB
- SHA256:
- 4cb77bc088b04fd69fe5a711356aec05e1a9d503b47e6e252a7f2577c7716a18
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.