Improve model card: Add detailed description, sample usage, and update paper link

README.md

@@ -1,13 +1,13 @@
 ---
-license: apache-2.0
 base_model: Wan-AI/Wan2.1-T2V-14B
+license: apache-2.0
+pipeline_tag: text-to-video
 tags:
 - text-to-video
 - diffusion
 - video-generation
 - turbodiffusion
 - wan2.1
-pipeline_tag: text-to-video
 ---
 
 <p align="center">
@@ -16,14 +16,31 @@ pipeline_tag: text-to-video
 
 # TurboWan2.1-T2V-14B-480P
 
-- This HuggingFace repo contains the `TurboWan2.1-T2V-14B-480P` model.
+This repository contains the `TurboWan2.1-T2V-14B-480P` model, part of the **TurboDiffusion** framework presented in [TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times](https://huggingface.co/papers/2512.16093). TurboDiffusion is a video generation acceleration framework that can speed up end-to-end diffusion generation by 100-200x while maintaining video quality.
 
 - For RTX 5090 or similar GPUs, please use the `TurboWan2.1-T2V-14B-480P-quant`. For other GPUs with a bigger GPU memory than 40GB, we recommend using `TurboWan2.1-T2V-14B-480P`.
 
-- For usage instructions, please see **https://github.com/thu-ml/TurboDiffusion**
+- For usage instructions and more details, please see the official GitHub repository: **https://github.com/thu-ml/TurboDiffusion**
+
+## Sample Usage
 
-- Paper: [TurboDiffusion: Accelerating Video Diffusion Models by 100-200 Times](https://arxiv.org/pdf/2512.16093)
+To run text-to-video inference using the `TurboWan2.1-T2V-1.3B-480P-quant` model, follow these steps. For full instructions, including downloading necessary VAE and text encoder checkpoints, refer to the [GitHub repository](https://github.com/thu-ml/TurboDiffusion#inference).
 
+```bash
+export PYTHONPATH=turbodiffusion
+
+# Example for Text-to-Video (T2V) inference
+python turbodiffusion/inference/wan2.1_t2v_infer.py \
+    --model Wan2.1-1.3B \
+    --dit_path checkpoints/TurboWan2.1-T2V-1.3B-480P-quant.pth \
+    --resolution 480p \
+    --prompt "A stylish woman walks down a Tokyo street filled with warm glowing neon and animated city signage. She wears a black leather jacket, a long red dress, and black boots, and carries a black purse. She wears sunglasses and red lipstick. She walks confidently and casually. The street is damp and reflective, creating a mirror effect of the colorful lights. Many pedestrians walk about." \
+    --num_samples 1 \
+    --num_steps 4 \
+    --quant_linear \
+    --attention_type sagesla \
+    --sla_topk 0.1
+```
 
 ## Citation
 ```
@@ -81,5 +98,4 @@ pipeline_tag: text-to-video
   journal={arXiv preprint arXiv:2505.11594},
   year={2025}
 }
-```
-
+```