Instructions to use hf-internal-testing/tiny-LTX2Pipeline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use hf-internal-testing/tiny-LTX2Pipeline with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-LTX2Pipeline", 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
File size: 667 Bytes
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"_class_name": "LTX2Pipeline",
"_diffusers_version": "0.39.0.dev0",
"audio_vae": [
"diffusers",
"AutoencoderKLLTX2Audio"
],
"connectors": [
"diffusers",
"LTX2TextConnectors"
],
"processor": [
null,
null
],
"scheduler": [
"diffusers",
"FlowMatchEulerDiscreteScheduler"
],
"text_encoder": [
"transformers",
"Gemma3ForConditionalGeneration"
],
"tokenizer": [
"transformers",
"GemmaTokenizerFast"
],
"transformer": [
"diffusers",
"LTX2VideoTransformer3DModel"
],
"vae": [
"diffusers",
"AutoencoderKLLTX2Video"
],
"vocoder": [
"diffusers",
"LTX2Vocoder"
]
}
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