Update README.md

README.md

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+---
+license: mit
+base_model:
+- Wan-AI/Wan2.1-T2V-1.3B
+pipeline_tag: text-to-video
+---
 <p align="center">
 <h1 align="center">HiAR</h1>
 <h3 align="center">Hierarchical Autoregressive Video Generation with Pipelined Parallel Inference</h3>
 </p>
 <p align="center">
-  <h3 align="center"><a href="#">Paper</a> | <a href="#">Website</a> | <a href="#">Models (HuggingFace)</a></h3>
+  <h3 align="center"><a href="#">Paper</a> | <a href="#">Website</a> </h3>
 </p>
 
 ---
 
 HiAR proposes **hierarchical denoising** for autoregressive video diffusion models, a paradigm shift from conventional block-first to **step-first** denoising order. By conditioning each block on context at a matched noise level, HiAR maximally attenuates error propagation while preserving temporal causality, achieving **state-of-the-art long video generation** (20s+) with significantly reduced quality drift.
-
-Key features:
-- **Hierarchical Denoising**: Step-first denoising order with noisy context conditioning at matched noise levels
-- **Pipelined Parallel Inference**: Exploits the hierarchical structure for wall-clock speedup via multi-GPU pipeline parallelism
-- **Forward-KL Regularization**: Prevents low-motion shortcuts in reverse-KL distillation
-- **4-step generation**: Real-time streaming video generation on a single GPU
-
----
-license: mit
----