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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Download README.md from Rin247/LTX-2.5-Diffusers: direct link, hf CLI and curl.
- Browser
- Download file 2.16 kB
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https://huggingface.co/Rin247/LTX-2.5-Diffusers/resolve/main/README.md
- Command line
-
hf download hf://Rin247/LTX-2.5-Diffusers/README.md
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curl -L -o README.md https://huggingface.co/Rin247/LTX-2.5-Diffusers/resolve/main/README.md
2.16 kB
| tags: | |
| - quantized | |
| - safetensors | |
| - diffusers | |
| - mecha | |
| - weight-only | |
| library_name: diffusers | |
| # LTX-2.5-Diffusers | |
| Quantised media packages of [Lightricks/LTX-2.5-Diffusers](https://huggingface.co/Lightricks/LTX-2.5-Diffusers). | |
| ## MECHA Forge | |
| MECHA — Model Engineering & Contextual Hearth Assembly | |
| These media packages have been forged and optimized in the MECHA Forge. | |
| ## Description | |
| LTX 2.5: text/image-to-video generation. 40 steps, CFG 3.0. Elaborate English prompts. | |
| ## Available quantizations | |
| | Quant | Denoiser | Text encoder | VAE | | |
| |---|---|---|---| | |
| | FP8 | FP8 | FP8 | FP8 | | |
| | INT8 | INT8 | INT8 | INT8 | | |
| | FP4 | FP4 | FP4 | FP8 | | |
| | INT4 | INT4 | INT4 | INT8 | | |
| The VAE is shared between formats: FP4 reuses the FP8 file, INT4 reuses the INT8 file. | |
| ## Components | |
| In addition to the denoiser, text encoder, and VAE, the package includes: | |
| - audio_vae, connectors, duration_head | |
| - latent_upsampler, temporal_latent_upsampler | |
| - prompt_enhancer, transformer_full | |
| - vocoder, scheduler, processor, tokenizer | |
| ## Recommended settings | |
| From the source model card (adjust to taste): | |
| | Parameter | Value | | |
| |---|---| | |
| | Steps | 30 | | |
| | CFG / Guidance scale | 3.0 | | |
| | Resolution | under 720x1280, <=257 frames | | |
| | Notes | Elaborate English prompts; negative prompt supported | | |
| ## Example prompts | |
| Caught in the moment (candid, slice of life): | |
| ``` | |
| masterpiece, best quality, highres, absurdres, very aesthetic, safe, 1man, solo, | |
| candid moment, natural lighting. A sunlit park bench in autumn, falling leaves, | |
| a bicycle leaning nearby, warm afternoon light. A 29-year-old man with platinum | |
| hair and blue eyes. He has an athletic build and a relaxed expression. He wears | |
| a denim jacket and jeans, holding a camera, mid-smile, candid and relaxed. | |
| ``` | |
| Fashion photography (magazine cover style): | |
| ``` | |
| Fashion film still: a 29-year-old woman with platinum hair, sharp cheekbones, | |
| and blue eyes; wearing a metallic silver gown, diamond earrings, stiletto heels; | |
| studio spotlight, motion blur, cinematic, 24fps, 8K. | |
| ``` | |
| Scenery: | |
| ``` | |
| Scenery: a sweeping drone shot of a fjord at sunset, golden light on water, | |
| mountains, clouds, boats, cinematic, 8K. | |
| ``` | |