readme: ---
  tags:
  - text-to-image
  - torch
  inference: false
  datasets:
  - laion/laion_100m_vqgan_f8
  ---
  
  This model is trained collaboratively — it is a part of the NeurIPS 2021 demonstration ["Training Transformers Together"](https://training-transformers-together.github.io/).
  
  The latest model checkpoint will be uploaded to this repository every 6 hours until the training stops.
  
  # Model Description 
  
  We train a model similar to [OpenAI DALL-E](https://openai.com/blog/dall-e/) — a Transformer model that generates images from text descriptions. Training happens collaboratively — volunteers from all over the Internet contribute to the training using hardware available to them. We use [LAION-400M](https://laion.ai/laion-400-open-dataset/), the world's largest openly available image-text-pair dataset with 400 million samples. Our model is based on the [dalle‑pytorch](https://github.com/lucidrains/DALLE-pytorch) implementation by [Phil Wang](https://github.com/lucidrains) with a few tweaks to make it communication-efficient. 
  
  # Training
  
  You can check our [dashboard](https://huggingface.co/spaces/training-transformers-together/Dashboard)  to see what is happening during the collaborative training (loss over time, number of active sessions over time, contribution of each participant, leaderboard, etc. ).
  
  # How to Use 
  
  You can start from our [Colab notebook for running inference](https://colab.research.google.com/drive/1Vkb-4nhEEH1a5vrKtpL4MTNiUTPdpPUl?usp=sharing).
  
  #  Limitations
  
  This model is created only as a demonstration of the new distributed training methods. **It should not be used for anything besides research purposes.**
  
  The authors have done only the most basic dataset filtering, so the model may be susceptible to biases in the training data and/or generate inappropriate content.
  
  At the moment, the model's generative capabilities are limited due to the absence of extensive experiments with the architecture and incomplete training.
  