Instructions to use optimum-intel-internal-testing/tiny-random-ltx2 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 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", 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 metadata.json from optimum-intel-internal-testing/tiny-random-ltx2: direct link, hf CLI and curl.
- Browser
- Download file 526 Bytes
-
https://huggingface.co/optimum-intel-internal-testing/tiny-random-ltx2/resolve/ov/metadata.json
- Command line
-
hf download hf://optimum-intel-internal-testing/tiny-random-ltx2@ov/metadata.json
-
curl -L -o metadata.json https://huggingface.co/optimum-intel-internal-testing/tiny-random-ltx2/resolve/ov/metadata.json
526 Bytes
| { | |
| "model_id": "optimum-intel-internal-testing/tiny-random-ltx2", | |
| "model_class": "OVLTX2Pipeline", | |
| "transformers_version": "5.10.4", | |
| "optimum_intel_version": "2.3.0.dev0+3329b15b", | |
| "openvino_version": "2026.5.0-23311-786052d995f", | |
| "generated_date": "2026-10-01", | |
| "components": [ | |
| "audio_vae_decoder/openvino_model.xml", | |
| "connectors/openvino_model.xml", | |
| "text_encoder/openvino_model.xml", | |
| "transformer/openvino_model.xml", | |
| "vae_decoder/openvino_model.xml", | |
| "vocoder/openvino_model.xml" | |
| ] | |
| } |