Instructions to use LiconStudio/LTX-2.3-Multiple-Subject-Reference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use LiconStudio/LTX-2.3-Multiple-Subject-Reference with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("LiconStudio/LTX-2.3-Multiple-Subject-Reference", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Thank you for this lora!
#4
by GDPR - opened
It works exceptionally well, even though you've labeled it as a test version. Would love to see some technical information how you came up with the idea and the training of the lora, if you plan to publish it :) Thanks!
It works exceptionally well, even though you've labeled it as a test version. Would love to see some technical information how you came up with the idea and the training of the lora, if you plan to publish it :) Thanks!
I will publish the detail technical information with the final version, Since there are still many aspects that need further optimization, the training strategy is still being adjusted and refined.