Instructions to use optimum-intel-internal-testing/tiny-random-ltx2.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use optimum-intel-internal-testing/tiny-random-ltx2.3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("optimum-intel-internal-testing/tiny-random-ltx2.3", 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 vae_decoder/openvino_model.bin from optimum-intel-internal-testing/tiny-random-ltx2.3: direct link, hf CLI and curl.
- Browser
- Download file 1.11 MB
-
https://huggingface.co/optimum-intel-internal-testing/tiny-random-ltx2.3/resolve/ov/vae_decoder/openvino_model.bin
- Command line
-
hf download hf://optimum-intel-internal-testing/tiny-random-ltx2.3@ov/vae_decoder/openvino_model.bin
-
curl -L -o openvino_model.bin https://huggingface.co/optimum-intel-internal-testing/tiny-random-ltx2.3/resolve/ov/vae_decoder/openvino_model.bin
1.11 MB
- Xet hash:
- 47c6647a31268b6de66c05d22ccc90cd2436b2bb4484a7015a3a270965d01e36
- Size of remote file:
- 1.11 MB
- SHA256:
- 915014e279f25aa294204daae91dd87e5379a0f34cbaf545973a2ece07ca2ac1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.