--- title: DALL路E mini emoji: 馃 colorFrom: yellow colorTo: green sdk: streamlit app_file: app/streamlit/app.py pinned: True --- # DALL路E Mini [![Join us on Discord](https://img.shields.io/discord/823813159592001537?color=5865F2&logo=discord&logoColor=white)](https://discord.gg/xBPBXfcFHd) _Generate images from a text prompt_ Our logo was generated with DALL路E mini using the prompt "logo of an armchair in the shape of an avocado". You can create your own pictures with [the demo](https://huggingface.co/spaces/flax-community/dalle-mini). ## How does it work? Refer to [our report](https://wandb.ai/dalle-mini/dalle-mini/reports/DALL-E-mini--Vmlldzo4NjIxODA). ## Inference Pipeline To generate sample predictions and understand the inference pipeline step by step, refer to [`tools/inference/inference_pipeline.ipynb`](tools/inference/inference_pipeline.ipynb). [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/borisdayma/dalle-mini/blob/main/tools/inference/inference_pipeline.ipynb) ## Contributing Join the community on the [DALLE-Pytorch Discord](https://discord.gg/xBPBXfcFHd). Any contribution is welcome, from reporting issues to proposing fixes/improvements or testing the model with cool prompts! ## Development ### Dependencies Installation For inference only, use `pip install git+https://github.com/borisdayma/dalle-mini.git`. For development, clone the repo and use `pip install -e ".[dev]"`. Before making a PR, check style with `make style`. ### Image Encoder We use a VQGAN from [taming-transformers](https://github.com/CompVis/taming-transformers), which can also be fine-tuned. Use [patil-suraj/vqgan-jax](https://github.com/patil-suraj/vqgan-jax) if you want to convert a checkpoint to JAX (does not support Gumbel). Any image encoder that turns an image into a fixed sequence of tokens can be used. ### Training of DALL路E mini Use [`tools/train/train.py`](tools/train/train.py). You can also adjust the [sweep configuration file](https://docs.wandb.ai/guides/sweeps) if you need to perform a hyperparameter search. ## FAQ ### Where to find the latest models? Trained models are on 馃 Model Hub: - [VQGAN-f16-16384](https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384) for encoding/decoding images - [DALL路E mini](https://huggingface.co/flax-community/dalle-mini) for generating images from a text prompt ### Where does the logo come from? 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. ## Acknowledgements - 馃 Hugging Face for organizing [the FLAX/JAX community week](https://github.com/huggingface/transformers/tree/master/examples/research_projects/jax-projects) - Google [TPU Research Cloud (TRC) program](https://sites.research.google/trc/) for providing computing resources - [Weights & Biases](https://wandb.com/) for providing the infrastructure for experiment tracking and model management ## Authors & Contributors DALL路E mini was initially developed by: - [Boris Dayma](https://github.com/borisdayma) - [Suraj Patil](https://github.com/patil-suraj) - [Pedro Cuenca](https://github.com/pcuenca) - [Khalid Saifullah](https://github.com/khalidsaifullaah) - [Tanishq Abraham](https://github.com/tmabraham) - [Ph煤c L锚 Kh岷痗](https://github.com/lkhphuc) - [Luke Melas](https://github.com/lukemelas) - [Ritobrata Ghosh](https://github.com/ghosh-r) Many thanks to the people who helped make it better: - the [DALLE-Pytorch](https://discord.gg/xBPBXfcFHd) and [EleutherAI](https://www.eleuther.ai/) communities for testing and exchanging cool ideas - [Rohan Anil](https://github.com/rohan-anil) for adding Distributed Shampoo optimizer ## Citing DALL路E mini If you find DALL路E mini useful in your research or wish to refer, please use the following BibTeX entry. ``` @misc{Dayma_DALL路E_Mini_2021, author = {Dayma, Boris and Patil, Suraj and Cuenca, Pedro and Saifullah, Khalid and Abraham, Tanishq and L锚 Kh岷痗, Ph煤c and Melas, Luke and Ghosh, Ritobrata}, doi = {10.5281/zenodo.5146400}, month = {7}, title = {DALL路E Mini}, url = {https://github.com/borisdayma/dalle-mini}, year = {2021} } ``` ## References ``` @misc{ramesh2021zeroshot, title={Zero-Shot Text-to-Image Generation}, author={Aditya Ramesh and Mikhail Pavlov and Gabriel Goh and Scott Gray and Chelsea Voss and Alec Radford and Mark Chen and Ilya Sutskever}, year={2021}, eprint={2102.12092}, archivePrefix={arXiv}, primaryClass={cs.CV} } ``` ``` @misc{esser2021taming, title={Taming Transformers for High-Resolution Image Synthesis}, author={Patrick Esser and Robin Rombach and Bj枚rn Ommer}, year={2021}, eprint={2012.09841}, archivePrefix={arXiv}, primaryClass={cs.CV} } ``` ``` @misc{lewis2019bart, title={BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension}, author={Mike Lewis and Yinhan Liu and Naman Goyal and Marjan Ghazvininejad and Abdelrahman Mohamed and Omer Levy and Ves Stoyanov and Luke Zettlemoyer}, year={2019}, eprint={1910.13461}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ``` @misc{radford2021learning, title={Learning Transferable Visual Models From Natural Language Supervision}, author={Alec Radford and Jong Wook Kim and Chris Hallacy and Aditya Ramesh and Gabriel Goh and Sandhini Agarwal and Girish Sastry and Amanda Askell and Pamela Mishkin and Jack Clark and Gretchen Krueger and Ilya Sutskever}, year={2021}, eprint={2103.00020}, archivePrefix={arXiv}, primaryClass={cs.CV} } ``` ``` @misc{anil2021scalable, title={Scalable Second Order Optimization for Deep Learning}, author={Rohan Anil and Vineet Gupta and Tomer Koren and Kevin Regan and Yoram Singer}, year={2021}, eprint={2002.09018}, archivePrefix={arXiv}, primaryClass={cs.LG} } ```