README.md

---
emoji: 🎥
title: 'RunAsh Wan 2.1 '
short_description: Real-time video generation
sdk: gradio
sdk_version: 5.34.2
license: apache-2.0
colorFrom: yellow
colorTo: red
pinned: true
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/6799f4b5a2b48413dd18a8dd/nxPqZaXa6quMBU4ojqDzC.png
---
# 🎬 RunAsh Real Time Video Generation

> *A real-time video generation model based on Wan 2.1 — optimized for low-latency inference and interactive applications.*

![Demo GIF or Screenshot Placeholder](https://via.placeholder.com/800x400?text=Real-Time+Video+Generation+Demo)

---

## 🧠 Model Overview

**RunAsh Real Time Video Generation** is a fine-tuned and optimized version of **Wan 2.1**, designed for **real-time video synthesis** from text prompts or image inputs. It leverages efficient architecture modifications and inference optimizations to enable smooth, interactive video generation at the edge or in-browser environments.

---

## 🚀 Features

- ✅ **Real-time generation** (target: <500ms per frame on GPU)
- ✅ **Text-to-Video** and **Image-to-Video** modes
- ✅ Low VRAM usage optimizations
- ✅ Interactive Gradio UI for live demos
- ✅ Supports variable length outputs (2s–8s clips)
- ✅ Plug-and-play with Hugging Face Spaces

---

## 🛠️ Technical Details

- **Base Model**: `Wan-2.1-RealTime` (by original authors)
- **Architecture**: Diffusion Transformer + Latent Consistency Modules
- **Resolution**: 576x320 (16:9) or 320x576 (9:16) — configurable
- **Frame Rate**: 24 FPS (adjustable)
- **Latency**: ~300–600ms per generation step (RTX 3090 / A10G)
- **Max Duration**: 8 seconds (configurable in code)

---

## 🖼️ Example Usage

### Text-to-Video

```python
prompt = "A cyberpunk cat riding a neon scooter through Tokyo at night"
video = pipeline(prompt, num_frames=48, guidance_scale=7.5)
```

### Image-to-Video

```python
init_image = load_image("cat.png")
video = pipeline(init_image, motion_prompt="zoom in slowly", num_frames=24)
```

---

## 🧪 Try It Out

👉 **Live Demo**: [https://huggingface.co/spaces/rammurmu/runash-realtime-video](https://huggingface.co/spaces/your-username/runash-realtime-video)

*Try generating short video clips in real time — no queue, no wait!*

---

## ⚙️ Installation & Local Use

```bash
git clone https://huggingface.co/spaces/rammurmu/runash-realtime-video
cd runash-realtime-video
pip install -r requirements.txt
python app.py
```

> Requires: Python 3.9+, PyTorch 2.0+, xFormers (optional), and a GPU with ≥8GB VRAM.

---

## 📜 License

This space is a derivative of **Wan 2.1 Real-time Video Generation**.

- **Original Model License**: Apache 2.0
- **This Space**: Licensed under the same terms as the original. For commercial use, please refer to the original authors’ terms.
- **Disclaimer**: This is a demonstration/educational fork. Not affiliated with original authors unless explicitly stated.

---

## 🙏 Attribution

This project is based on:

> **Wan 2.1 Real-time Video Generation**  
> Authors: Ram Murmu RunAsh AI  
> Hugging Face Link: [https://huggingface.co/spaces/wan-2.1](https://huggingface.co/spaces/wan-2.1)  
> Paper: [Link to Paper, if available]

---

## 💬 Feedback & Support

Found a bug? Want a feature?  
→ Open an [Issue](https://github.com/your-org/runash-video/issues)  
→ Join our [Discord](https://discord.gg/your-invite-link)  
→ Tweet at [@RunAsh AI Labs](https://twitter.com/RunAsh_AI)

---

## 🌟 Star This Repo

If you find this useful, please ⭐️ the original Wan 2.1 repo and this space!

---

## 📌 Disclaimer

This is a **duplicate/forked space** for demonstration and community experimentation. All credit for the underlying model goes to the original Wan 2.1 authors. This space does not claim original authorship of the core model.

---

✅ **Updated**: April 2025  
🧑‍💻 **Maintained by**: RunAsh AI Labs  
📬 ** Contact**: [[email protected]](mailto:[email protected])
---