Instructions to use Rin247/LTX-2.5-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Rin247/LTX-2.5-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Rin247/LTX-2.5-Diffusers", 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
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README.md
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@@ -36,3 +36,14 @@ In addition to the denoiser, text encoder, and VAE, the package includes:
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- latent_upsampler, temporal_latent_upsampler
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- prompt_enhancer, transformer_full
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- vocoder, scheduler, processor, tokenizer
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- latent_upsampler, temporal_latent_upsampler
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- prompt_enhancer, transformer_full
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- vocoder, scheduler, processor, tokenizer
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## Recommended settings
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Starting points (adjust to taste; see the source model card for authoritative values):
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| Parameter | Value |
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|---|---|
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| Steps | 30 |
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| CFG / Guidance scale | 3.0 |
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| Resolution | 768x512 |
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| Notes | Video |
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