# oasis

**Repository Path**: Unity-Technologies/oasis

## Basic Information

- **Project Name**: oasis
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2024-11-05
- **Last Updated**: 2024-11-05

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Oasis 500M

![](./media/arch.png)

![](./media/thumb.png)

Oasis is an interactive world model developed by [Decart](https://www.decart.ai/) and [Etched](https://www.etched.com/). Based on diffusion transformers, Oasis takes in user keyboard input and generates gameplay in an autoregressive manner. We release the weights for Oasis 500M, a downscaled version of the model, along with inference code for action-conditional frame generation. 

For more details, see our [joint blog post](https://oasis-model.github.io/) to learn more.

And to use the most powerful version of the model, be sure to check out the [live demo](https://oasis.us.decart.ai/) as well!

## Setup
```
git clone https://github.com/etched-ai/open-oasis.git
cd open-oasis
# Install pytorch
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu121
# Install other dependencies
pip install einops diffusers timm av
```

## Download the model weights
Inside the `open-oasis/` directory, run:
```
huggingface-cli login
huggingface-cli download Etched/oasis-500m oasis500m.safetensors # DiT checkpoint
huggingface-cli download Etched/oasis-500m vit-l-20.safetensors  # ViT VAE checkpoint
```

## Basic Usage
We include a basic inference script that loads a prompt frame from a video and generates additional frames conditioned on actions.
```
python generate.py
```
The resulting video will be saved to `video.mp4`. Here's are some examples of a generation from this 500M model!

![](media/sample_0.gif)
![](media/sample_1.gif)

> Hint: try swapping out the `.mp4` input file in the script to try different environments!