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---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo_share.png?raw=true
tags:
- exbert
- 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/1108502565925326850/zPsBf2BI_normal.png')">
</div>
<div style="margin-top: 8px; font-size: 19px; font-weight: 800">Julien Chaumond 🤖 AI Bot </div>
<div style="font-size: 15px; color: #657786">@julien_c 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)!
<a href="https://huggingface.co/exbert/?model=huggingtweets/julien_c&modelKind=autoregressive&sentence=I%20love%20huggingtweets!&layer=11">
<img width="300px" src="https://hf-dinosaur.huggingface.co/exbert/button.png">
</a>
## 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://bit.ly/2TGXMZf).
## Training data
The model was trained on [@julien_c's tweets](https://twitter.com/julien_c).
| Data | Quantity |
|-------------------|--------------|
| Tweets downloaded | 3213 |
| Retweets | 874 |
| Short tweets | 224 |
| Tweets kept | 2115 |
[Explore the data](https://app.wandb.ai/borisd13/huggingtweets/runs/223974hk/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 @julien_c's tweets for 4 epochs.
Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/borisd13/huggingtweets/runs/3axlm217).
## Intended uses & limitations
#### 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/julien_c')
generator("My dream is", max_length=50, 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/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)