File size: 2,072 Bytes
943e763 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | ---
base_model:
- Lightricks/LTX-Video-0.9.5
library_name: diffusers
tags:
- ltx-video
- text-to-video
- candle
- rust
- gguf
- oxide-lab
- safetensors
language:
- en
license: other
pipeline_tag: text-to-video
---
# LTX-Video in Rust (Candle)
This repository provides a high-performance, native Rust implementation of [LTX-Video](https://huggingface.co/Lightricks/LTX-Video) using the [Candle](https://github.com/huggingface/candle) ML framework.
## Features
- 🦀 **Native Rust**: No Python dependency required for inference.
- 🚀 **Performance**: Optimized for NVIDIA GPUs with **Flash Attention v2** and **cuDNN**.
- 💾 **Memory Efficient**: Supports **GGUF quantization** for T5-XXL text encoder and **VAE tiling/slicing** for generating HD videos on consumer GPUs.
- 🛠 **Flexible**: Easy to use CLI for video generation and library for custom integration.
## Quick Start
### Installation
Ensure you have Rust and the CUDA Toolkit installed, then:
```bash
git clone https://github.com/FerrisMind/candle-video
cd candle-video
cargo build --release --features flash-attn,cudnn
```
### Video Generation
```bash
cargo run --example ltx-video --release -- \
--local-weights ./models/ltx-video \
--prompt "A serene mountain lake at sunset, photorealistic, 4k" \
--width 768 --height 512 --num-frames 97 \
--steps 30
```
## Performance & Memory
| Resolution | Frames | VRAM (BF16) | VRAM (VAE Tiling) |
|------------|--------|-------------|-------------------|
| 512x768 | 97 | ~8-13 GB | ~8-9 GB |
*Note: Using GGUF T5 encoder saves an additional ~8-12GB of VRAM.*
## Credits
- **Original Model**: [Lightricks/LTX-Video](https://huggingface.co/Lightricks/LTX-Video)
- **Framework**: [HuggingFace Candle](https://github.com/huggingface/candle)
- **T5 v1_1 XXl GGUF and Safetensors**: [city96/LTX-Video-gguf](https://huggingface.co/city96/LTX-Video-gguf) (for GGUF support patterns, T5 XXl GGUF and Safetensors)
---
For more details, visit the main [GitHub Repository](https://github.com/FerrisMind/candle-video). |