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", torch_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
MIX with Ic-Lora?
#29
by Spaconi - opened
Hi there, I can't find any way to mix this with my Ic-Loras for v2v workflow, I need to increase my character swap likeness but don't know how to do it! Can you please tell me if it's possibile?
Hi there, I can't find any way to mix this with my Ic-Loras for v2v workflow, I need to increase my character swap likeness but don't know how to do it! Can you please tell me if it's possibile?
Because this LoRA uses a rather鐗规畩 training approach, it may conflict with many other LoRAs. You鈥檒l need to test the combination yourself to see whether they work together properly.