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--- |
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title: DALL路E mini |
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emoji: 馃 |
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colorFrom: red |
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colorTo: purple |
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sdk: streamlit |
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app_file: app/app.py |
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pinned: false |
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--- |
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# DALL路E Mini |
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_Generate images from a text prompt_ |
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<img src="img/logo.png" width="200"> |
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Our logo was generated with DALL路E mini using the prompt "logo of an armchair in the shape of an avocado". |
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You can create your own pictures with [the demo](https://huggingface.co/spaces/flax-community/dalle-mini) (temporarily in beta on Huging Face Spaces but soon to be open to all). |
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## How does it work? |
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Refer to [our report](https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA). |
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## Where does the logo come from? |
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The "armchair in the shape of an avocado" was used by OpenAI when releasing DALL路E to illustrate the model's capabilities. Having successful predictions on this prompt represents a big milestone to us. |
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## Development |
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This section is for the adventurous people wanting to look into the code. |
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### Dependencies Installation |
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The root folder and associated `requirements.txt` is only for the app. |
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You will find necessary requirements in each sub-section. |
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You should create a new python virtual environment and install the project dependencies inside the virtual env. You need to use the `-f` (`--find-links`) option for `pip` to be able to find the appropriate `libtpu` required for the TPU hardware. |
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Adapt the installation to your own hardware and follow library installation instructions. |
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``` |
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$ pip install -r requirements.txt -f https://storage.googleapis.com/jax-releases/libtpu_releases.html |
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``` |
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If you use `conda`, you can create the virtual env and install everything using: `conda env update -f environments.yaml` |
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### Training of VQGAN |
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The VQGAN was trained using [taming-transformers](https://github.com/CompVis/taming-transformers). |
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We recommend using the latest version available. |
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### Conversion of VQGAN to JAX |
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Use [patil-suraj/vqgan-jax](https://github.com/patil-suraj/vqgan-jax). |
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### Training of Seq2Seq |
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Refer to `dev/seq2seq` folder. |
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You can also adjust the [sweep configuration file](https://docs.wandb.ai/guides/sweeps) if you need to perform a hyperparameter search. |
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### Inference |
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Refer to `dev/notebooks/demo`. |
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## Authors |
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- [Boris Dayma](https://github.com/borisdayma) |
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- [Suraj Patil](https://github.com/patil-suraj) |
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- [Pedro Cuenca](https://github.com/pcuenca) |
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- [Khalid Saifullah](https://github.com/khalidsaifullaah) |
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- [Tanishq Abraham](https://github.com/tmabraham) |
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- [Ph煤c L锚 Kh岷痗](https://github.com/lkhphuc) |
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- [Luke Melas](https://github.com/lukemelas) |
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- [Ritobrata Ghosh](https://github.com/ghosh-r) |
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## Acknowledgements |
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- 馃 Hugging Face for organizing [the FLAX/JAX community week](https://github.com/huggingface/transformers/tree/master/examples/research_projects/jax-projects) |
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- Google Cloud team for providing access to TPU's |
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