Instructions to use wolf1280/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 wolf1280/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("wolf1280/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_V2/02/V1.mp4 from wolf1280/LTX-2.3-Multiple-Subject-Reference: direct link, hf CLI and curl.
- Browser
- Download file 4.25 MB
-
https://huggingface.co/wolf1280/LTX-2.3-Multiple-Subject-Reference/resolve/main/Validition_V2/02/V1.mp4
- Command line
-
hf download hf://wolf1280/LTX-2.3-Multiple-Subject-Reference/Validition_V2/02/V1.mp4
-
curl -L -o V1.mp4 https://huggingface.co/wolf1280/LTX-2.3-Multiple-Subject-Reference/resolve/main/Validition_V2/02/V1.mp4
4.25 MB
- Xet hash:
- 5c81ce0de512f7e9255bc8fbd143f68e2d100725a9f98a27d2393d6654521053
- Size of remote file:
- 4.25 MB
- SHA256:
- 5e1d40370bb31afcade4ae3ed7c3c3bbed2142c7b3fae878bffab3e43fa068b6
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