---
language: en
thumbnail: http://www.huggingtweets.com/apesahoy-daftlimmy-women4wes/1662819834805/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

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            style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1196519479364268034/5QpniWSP_400x400.jpg&#39;)">
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            style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profile_images/1489315073055199233/O-Sws7Go_400x400.jpg&#39;)">
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    <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">🤖 AI CYBORG 🤖</div>
    <div style="text-align: center; font-size: 16px; font-weight: 800">twitch.tv/Limmy & Humongous Ape MP & Women for Wes</div>
    <div style="text-align: center; font-size: 14px;">@apesahoy-daftlimmy-women4wes</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 tweets from twitch.tv/Limmy & Humongous Ape MP & Women for Wes.

| Data | twitch.tv/Limmy | Humongous Ape MP | Women for Wes |
| --- | --- | --- | --- |
| Tweets downloaded | 3246 | 3247 | 1807 |
| Retweets | 411 | 191 | 53 |
| Short tweets | 715 | 607 | 275 |
| Tweets kept | 2120 | 2449 | 1479 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/6goa6gdz/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 @apesahoy-daftlimmy-women4wes's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/ltv5351j) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/ltv5351j/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/apesahoy-daftlimmy-women4wes')
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)