readme: ---
  language: en
  thumbnail: https://www.huggingtweets.com/arsonatdennys/1620019020010/predictions.png
  tags:
  - huggingtweets
  widget:
  - text: "My dream is"
  ---
  
  <div>
  <div style="width: 132px; height:132px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1383564179471175680/xALN4Z-R_400x400.jpg')">
  </div>
  <div style="margin-top: 8px; font-size: 19px; font-weight: 800">Aster, internet archaeologist 🤖 AI Bot </div>
  <div style="font-size: 15px">@arsonatdennys bot</div>
  </div>
  
  I was made with [huggingtweets](https://github.com/borisdayma/huggingtweets).
  
  Create your own bot based on your favorite user with [the demo](https://colab.research.google.com/github/borisdayma/huggingtweets/blob/master/huggingtweets-demo.ipynb)!
  
  ## How does it work?
  
  The model uses the following pipeline.
  
  ![pipeline](https://github.com/borisdayma/huggingtweets/blob/master/img/pipeline.png?raw=true)
  
  To understand how the model was developed, check the [W&B report](https://wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-Model-to-Generate-Tweets--VmlldzoxMTY5MjI).
  
  ## Training data
  
  The model was trained on [@arsonatdennys's tweets](https://twitter.com/arsonatdennys).
  
  | Data | Quantity |
  | --- | --- |
  | Tweets downloaded | 3207 |
  | Retweets | 1561 |
  | Short tweets | 223 |
  | Tweets kept | 1423 |
  
  [Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2rggt8p2/artifacts), which is tracked with [W&B artifacts](https://docs.wandb.com/artifacts) at every step of the pipeline.
  
  ## Training procedure
  
  The model is based on a pre-trained [GPT-2](https://huggingface.co/gpt2) which is fine-tuned on @arsonatdennys's tweets.
  
  Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/350x43du) for full transparency and reproducibility.
  
  At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/350x43du/artifacts) is logged and versioned.
  
  ## How to use
  
  You can use this model directly with a pipeline for text generation:
  
  ```python
  from transformers import pipeline
  generator = pipeline('text-generation',
                       model='huggingtweets/arsonatdennys')
  generator("My dream is", num_return_sequences=5)
  ```
  
  ## Limitations and bias
  
  The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).
  
  In addition, the data present in the user's tweets further affects the text generated by the model.
  
  ## About
  
  *Built by Boris Dayma*
  
  [![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)
  
  For more details, visit the project repository.
  
  [![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)
  