Instructions to use FenomAI/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 FenomAI/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("FenomAI/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
Download validition_v1/03/video.mp4 from FenomAI/LTX-2.3-Multiple-Subject-Reference: direct link, hf CLI and curl.
- Browser
- Download file 1.67 MB
-
https://huggingface.co/FenomAI/LTX-2.3-Multiple-Subject-Reference/resolve/main/validition_v1/03/video.mp4
- Command line
-
hf download hf://FenomAI/LTX-2.3-Multiple-Subject-Reference/validition_v1/03/video.mp4
-
curl -L -o video.mp4 https://huggingface.co/FenomAI/LTX-2.3-Multiple-Subject-Reference/resolve/main/validition_v1/03/video.mp4
1.67 MB
- Xet hash:
- d190a2175c65a3adba7dc246ff9baf2a50fb4a4d9223e47083efc79a6adf0920
- Size of remote file:
- 1.67 MB
- SHA256:
- fc885f1b5341c6288bce31f3a9565a677a0b2019fff09a9d0e08657f6798489b
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