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---
title: Krea Realtime Video  T2V ZeroGPU
emoji: 🎬
colorFrom: blue
colorTo: purple
sdk: gradio
app_file: app.py
pinned: false
hardware: zerogpu
python_version: "3.10.13"
---

# Krea Realtime Video

A Hugging Face Space for generating short videos with [`krea/krea-realtime-video`](https://huggingface.co/krea/krea-realtime-video), using Diffusers `ModularPipeline` and ZeroGPU.

This demo runs local text-to-video inference inside the Space and includes optional LoRA support for the Origami style.

## Features

- Text-to-video generation with Krea Realtime Video 14B
- Diffusers `ModularPipeline` integration
- ZeroGPU-compatible runtime
- Manual style loading before generation
- Optional Origami LoRA support
- Automatic `[origami]` trigger insertion when the Origami style is active
- Adjustable video length and quality controls
- Progress feedback during generation

## How to use

1. Enter a prompt describing the video you want to generate.
2. Optionally select a style.
3. If you select **Origami**, click **Load style** before generating.
4. Adjust:
   - **Length**: number of video blocks
   - **Quality**: inference steps per block
   - **Seed**: reproducibility seed
5. Click **Generate video**.

The generated video will appear on the right side of the interface.

## Styles

### Base model

Uses the original Krea Realtime Video model without any additional LoRA.

### Origami

Uses the Origami LoRA adapter:

[`shauray/Origami_WanLora`](https://huggingface.co/shauray/Origami_WanLora)

When this style is active, the app automatically prefixes the prompt with:

```text
[origami]
```

For example, this prompt:

```text
a cat sitting on a boat
```

is internally sent as:

```text
[origami] a cat sitting on a boat
```

## Recommended settings

For a balanced result:

```text
Length: 9
Quality: 6
Seed: any fixed integer
```

Lower values generate faster. Higher values may improve temporal consistency and visual quality, but can take longer.

## Example prompts

```text
Astronaut in a jungle, cold color palette, muted colors, detailed, cinematic, 8k
```

```text
A tiny wooden boat drifting through a misty lake at sunrise, a curious cat sitting at the front, soft cinematic lighting, calm water reflections
```

```text
A futuristic city at sunset, flying vehicles between glass towers, neon reflections, cinematic camera movement, atmospheric haze
```

```text
A car racing down a snowy mountain road, dramatic chase shot, powder snow flying behind the wheels, cold blue lighting, high speed motion
```

```text
A surreal underwater library, glowing jellyfish floating between bookshelves, slow cinematic dolly shot, dreamlike atmosphere
```

Origami examples:

```text
a cat sitting on a boat
```

```text
a dragon flying over a mountain village at sunrise, paper-folded geometry, delicate handmade texture, soft shadows
```

```text
a small fox walking through a paper forest, handcrafted origami style, warm lantern light, cinematic close-up
```

## Implementation notes

This Space uses a ZeroGPU compatibility path.

The original optimized inference path for Krea Realtime Video relies on features such as `torch.compile` and optimized attention kernels. In this Space, `torch.compile` is intentionally disabled to keep the runtime compatible with ZeroGPU.

The model is loaded when the Space starts. LoRA styles are loaded manually through the UI before generation, so the generation step can focus on inference.

## Limitations

- The demo is intended for short video generation.
- Very long generations may be slower or less stable.
- The Origami style must be loaded once before it can be used.
- LoRA strength control is not exposed in the UI because the current adapter API used by this runtime does not reliably support per-adapter weights.
- ZeroGPU compatibility may be slower than a fully optimized dedicated GPU deployment.

## Model

Base model:

[`krea/krea-realtime-video`](https://huggingface.co/krea/krea-realtime-video)

Optional LoRA:

[`shauray/Origami_WanLora`](https://huggingface.co/shauray/Origami_WanLora)

## Acknowledgements

This Space is built on top of the Hugging Face ecosystem, including Diffusers, Gradio, PEFT, and the Hugging Face Hub.