Update README.md

README.md

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----
-license: apache-2.0
----
+---
+base_model:
+- Lightricks/LTX-Video-0.9.5
+library_name: candle
+tags:
+- ltx-video
+- text-to-video
+- candle
+- rust
+- gguf
+language:
+- en
+license: apache-2.0
+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     | ~8-12 GB      | ~8 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)
+- **Inspiration**: [city96/LTX-Video-gguf](https://huggingface.co/city96/LTX-Video-gguf) (for GGUF support patterns)
+
+---
+For more details, visit the main [GitHub Repository](https://github.com/FerrisMind/candle-video).