Instructions to use B4100/LTXBJ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use B4100/LTXBJ with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("lynaNSFW/LTX2.3_NSFW_motion", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("B4100/LTXBJ") prompt = "-" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| tags: | |
| - text-to-image | |
| - lora | |
| - diffusers | |
| - template:diffusion-lora | |
| widget: | |
| - output: | |
| url: images/barflashshot.png | |
| text: '-' | |
| base_model: lynaNSFW/LTX2.3_NSFW_motion | |
| instance_prompt: She is performing oral sex on him | |
| # LTXBJ | |
| <Gallery /> | |
| ## Model description | |
| Trigger - She is performing oral sex on him. | |
| ## Trigger words | |
| You should use `She is performing oral sex on him` to trigger the image generation. | |
| ## Download model | |
| [Download](/B4100/LTXBJ/tree/main) them in the Files & versions tab. | |