---
language: en
thumbnail: https://www.huggingtweets.com/xescobin/1608382856568/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

xean 🤖 AI Bot

@xescobin bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@xescobin's tweets](https://twitter.com/xescobin).

Data
Quantity

Tweets downloaded
848

Retweets
51

Short tweets
213

Tweets kept
584

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3tc2mjf0/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 @xescobin's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2gvtor1n) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2gvtor1n/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/xescobin')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/ddlcquotes/1612815814568/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

ddlc quote bot 🤖 AI Bot

@ddlcquotes bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@ddlcquotes's tweets](https://twitter.com/ddlcquotes).

Data
Quantity

Tweets downloaded
3203

Retweets
0

Short tweets
27

Tweets kept
3176

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3vugceit/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 @ddlcquotes's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1rh6mzov) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1rh6mzov/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/ddlcquotes')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/sburhanova/1618946732960/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Сабинэлла 🤖 AI Bot

@sburhanova bot

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 [@sburhanova's tweets](https://twitter.com/sburhanova).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3174 |
| Retweets | 147 |
| Short tweets | 389 |
| Tweets kept | 2638 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/24qx8h9j/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 @sburhanova's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/xpxepnde/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/sburhanova')
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)


---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Strife 🤖 AI Bot

@strife212 bot

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 [@strife212's tweets](https://twitter.com/strife212).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3245 |
| Retweets | 78 |
| Short tweets | 1147 |
| Tweets kept | 2020 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3kipxik1/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 @strife212's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/nh0ek96v) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/nh0ek96v/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/strife212')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/codewisdom/1629833911172/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Programming Wisdom

@codewisdom

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 Programming Wisdom.

| Data | Programming Wisdom |
| --- | --- |
| Tweets downloaded | 3249 |
| Retweets | 601 |
| Short tweets | 68 |
| Tweets kept | 2580 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1v0fkmjn/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 @codewisdom's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1oohyzx0) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1oohyzx0/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/codewisdom')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/opolopso/1614137253464/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

caroline ◍•ᴗ•◍ 🤖 AI Bot

@opolopso bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@opolopso's tweets](https://twitter.com/opolopso).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 1569 |
| Retweets | 373 |
| Short tweets | 278 |
| Tweets kept | 918 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/43enov0e/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 @opolopso's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/6ix3af62) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/6ix3af62/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/opolopso')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/taylorswift13/1601921729296/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

Taylor Swift 🤖 AI Bot

@taylorswift13 bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@taylorswift13's tweets](https://twitter.com/taylorswift13).

Data
Quantity

Tweets downloaded
523

Retweets
79

Short tweets
77

Tweets kept
367

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/21sm4nue/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 @taylorswift13's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/2xak8xin) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/2xak8xin/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/taylorswift13')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/verafiedposter/1616696054193/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

big black cloud will come 🤖 AI Bot

@verafiedposter bot

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 [@verafiedposter's tweets](https://twitter.com/verafiedposter).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3222 |
| Retweets | 226 |
| Short tweets | 234 |
| Tweets kept | 2762 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2byyqoj9/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 @verafiedposter's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/27jpl5l8) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/27jpl5l8/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/verafiedposter')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/staenrey/1616807818255/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Staenrey | Please Help Belarus 🤖 AI Bot

@staenrey bot

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 [@staenrey's tweets](https://twitter.com/staenrey).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3206 |
| Retweets | 412 |
| Short tweets | 268 |
| Tweets kept | 2526 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3n21i0qf/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 @staenrey's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2vt46tmy) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2vt46tmy/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/staenrey')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/oliversherouse/1607051207212/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

Oliver Sherouse 🤖 AI Bot

@oliversherouse bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@oliversherouse's tweets](https://twitter.com/oliversherouse).

Data
Quantity

Tweets downloaded
84

Retweets
15

Short tweets
7

Tweets kept
62

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2xs14x8e/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 @oliversherouse's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/30zp73af) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/30zp73af/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/oliversherouse')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/freudotheism/1625867628365/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Evelyn🪶🇰🇵

@freudotheism

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 Evelyn🪶🇰🇵.

| Data | Evelyn🪶🇰🇵 |
| --- | --- |
| Tweets downloaded | 3231 |
| Retweets | 333 |
| Short tweets | 968 |
| Tweets kept | 1930 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3rbzyyts/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 @freudotheism's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/elt06ed5) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/elt06ed5/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/freudotheism')
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)


---
language: en
thumbnail: http://res.cloudinary.com/huggingtweets/image/upload/v1599944612/nntaleb.jpg
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

Nassim Nicholas Taleb 🤖 AI Bot

@nntaleb bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@nntaleb's tweets](https://twitter.com/nntaleb).

Data
Quantity

Tweets downloaded
3213

Retweets
274

Short tweets
404

Tweets kept
2535

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/1r6ljy96/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 @nntaleb's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/1iqho166) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/1iqho166/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/nntaleb')
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/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)


---
language: en
thumbnail: http://www.huggingtweets.com/yu_kisub21/1643037750346/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

ゆう🇲🇾英語を軸に人生に革新を🔥

@yu_kisub21

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 ゆう🇲🇾英語を軸に人生に革新を🔥.

| Data | ゆう🇲🇾英語を軸に人生に革新を🔥 |
| --- | --- |
| Tweets downloaded | 1580 |
| Retweets | 366 |
| Short tweets | 1137 |
| Tweets kept | 77 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1fswx6qh/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 @yu_kisub21's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/35tec8b2) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/35tec8b2/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/yu_kisub21')
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)


---
language: en
thumbnail: http://www.huggingtweets.com/cobie-coinerstakingls/1643368738479/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Crypto Bros Taking Ls & Cobie

@cobie-coinerstakingls

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 Crypto Bros Taking Ls & Cobie.

| Data | Crypto Bros Taking Ls | Cobie |
| --- | --- | --- |
| Tweets downloaded | 566 | 3248 |
| Retweets | 94 | 93 |
| Short tweets | 222 | 500 |
| Tweets kept | 250 | 2655 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1gjf29z1/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 @cobie-coinerstakingls's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/c8xc9umf) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/c8xc9umf/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/cobie-coinerstakingls')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/lily_dusk/1620679618807/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Lily Dusk 🎀 | EN VTuber

@lily_dusk

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 Lily Dusk 🎀 | EN VTuber.

| Data | Lily Dusk 🎀 | EN VTuber |
| --- | --- |
| Tweets downloaded | 3240 |
| Retweets | 608 |
| Short tweets | 1143 |
| Tweets kept | 1489 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3u2l8fdu/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 @lily_dusk's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1f9vw2da) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1f9vw2da/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/lily_dusk')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/august77lng/1614115355848/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Himboclese,,,, of ACAB 🤖 AI Bot

@august77lng bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@august77lng's tweets](https://twitter.com/august77lng).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3151 |
| Retweets | 2357 |
| Short tweets | 114 |
| Tweets kept | 680 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3ly74f65/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 @august77lng's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3ck3jotc) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3ck3jotc/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/august77lng')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/artstarcross/1627659166884/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Starcross

@artstarcross

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 Starcross.

| Data | Starcross |
| --- | --- |
| Tweets downloaded | 1846 |
| Retweets | 217 |
| Short tweets | 67 |
| Tweets kept | 1562 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/177l3jal/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 @artstarcross's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2w1qo4hm) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2w1qo4hm/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/artstarcross')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/cryptolith_-poaststructural-rusticgendarme/1627059554644/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

merz & 🏁🗼 & severian

@cryptolith_-poaststructural-rusticgendarme

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 merz & 🏁🗼 & severian.

| Data | merz | 🏁🗼 | severian |
| --- | --- | --- | --- |
| Tweets downloaded | 2456 | 3223 | 3226 |
| Retweets | 424 | 450 | 358 |
| Short tweets | 416 | 1017 | 577 |
| Tweets kept | 1616 | 1756 | 2291 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2t7za49v/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 @cryptolith_-poaststructural-rusticgendarme's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/txcxy9qk) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/txcxy9qk/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/cryptolith_-poaststructural-rusticgendarme')
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)


---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

KitsuneSpirit🦊💝 VTuber ~

@kitsune__spirit

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 KitsuneSpirit🦊💝 VTuber ~.

| Data | KitsuneSpirit🦊💝 VTuber ~ |
| --- | --- |
| Tweets downloaded | 3250 |
| Retweets | 65 |
| Short tweets | 998 |
| Tweets kept | 2187 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3qfz2kzl/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 @kitsune__spirit's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2mrv13gz) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2mrv13gz/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/kitsune__spirit')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/dannybarefoot/1624927497917/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Danny Barefoot

@dannybarefoot

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 Danny Barefoot.

| Data | Danny Barefoot |
| --- | --- |
| Tweets downloaded | 909 |
| Retweets | 168 |
| Short tweets | 124 |
| Tweets kept | 617 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/7awrd5uh/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 @dannybarefoot's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/33cmwhib) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/33cmwhib/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/dannybarefoot')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/factfictyoutube/1627537153556/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Factually Fictitious

@factfictyoutube

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 Factually Fictitious.

| Data | Factually Fictitious |
| --- | --- |
| Tweets downloaded | 3211 |
| Retweets | 957 |
| Short tweets | 134 |
| Tweets kept | 2120 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/b5r6jmml/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 @factfictyoutube's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/31b4bo7z) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/31b4bo7z/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/factfictyoutube')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/kanganateam/1613324975942/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Kangana Ranaut 🤖 AI Bot

@kanganateam bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@kanganateam's tweets](https://twitter.com/kanganateam).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3167 |
| Retweets | 1321 |
| Short tweets | 67 |
| Tweets kept | 1779 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3gxbb7zk/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 @kanganateam's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/28k6gjhm) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/28k6gjhm/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/kanganateam')
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)


---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo_share.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

Victor Sanh 🤖 AI Bot

@sanhestpasmoi bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@sanhestpasmoi's tweets](https://twitter.com/sanhestpasmoi).

Data
Quantity

Tweets downloaded
957

Retweets
375

Short tweets
35

Tweets kept
547

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/1uhcy43z/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 @sanhestpasmoi's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/2m1a68n0) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/2m1a68n0/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/sanhestpasmoi')
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/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)


---
language: en
thumbnail: http://www.huggingtweets.com/elxokas-evilafm-ibaillanos/1641757124234/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Ibai & Alexelcapo & XOKAS

@elxokas-evilafm-ibaillanos

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 Ibai & Alexelcapo & XOKAS.

| Data | Ibai | Alexelcapo | XOKAS |
| --- | --- | --- | --- |
| Tweets downloaded | 3250 | 3207 | 3245 |
| Retweets | 28 | 12 | 187 |
| Short tweets | 669 | 231 | 421 |
| Tweets kept | 2553 | 2964 | 2637 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/ed2k4vcn/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 @elxokas-evilafm-ibaillanos's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/169fwvwo) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/169fwvwo/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/elxokas-evilafm-ibaillanos')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/deepleffen-dril/1628834161509/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Deep Leffen Bot & wint

@deepleffen-dril

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 Deep Leffen Bot & wint.

| Data | Deep Leffen Bot | wint |
| --- | --- | --- |
| Tweets downloaded | 506 | 3209 |
| Retweets | 13 | 463 |
| Short tweets | 26 | 311 |
| Tweets kept | 467 | 2435 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/29zfoi4y/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 @deepleffen-dril's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2fygim56) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2fygim56/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/deepleffen-dril')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/naisu9k/1631835118534/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

naisu

@naisu9k

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 naisu.

| Data | naisu |
| --- | --- |
| Tweets downloaded | 3211 |
| Retweets | 1023 |
| Short tweets | 424 |
| Tweets kept | 1764 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/84y08bav/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 @naisu9k's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/jtnpwkvw/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/naisu9k')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/punk_bat/1617789457426/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Bat of many knives 🤖 AI Bot

@punk_bat bot

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 [@punk_bat's tweets](https://twitter.com/punk_bat).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3221 |
| Retweets | 1399 |
| Short tweets | 487 |
| Tweets kept | 1335 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2bc1j6ct/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 @punk_bat's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/xer8gy05) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/xer8gy05/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/punk_bat')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/neil_jetter/1616624365889/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Puzzle man 🧩 🤖 AI Bot

@neil_jetter bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@neil_jetter's tweets](https://twitter.com/neil_jetter).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 481 |
| Retweets | 117 |
| Short tweets | 96 |
| Tweets kept | 268 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/39dpbluj/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 @neil_jetter's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3a7kufsc) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3a7kufsc/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/neil_jetter')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/rcandlemaker/1627056132386/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Ronnie The Candlemaker

@rcandlemaker

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 Ronnie The Candlemaker.

| Data | Ronnie The Candlemaker |
| --- | --- |
| Tweets downloaded | 198 |
| Retweets | 0 |
| Short tweets | 2 |
| Tweets kept | 196 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3nibje1t/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 @rcandlemaker's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/4z5spadd) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/4z5spadd/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/rcandlemaker')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/926stories/1623134303273/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Rummyyyy

@926stories

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 Rummyyyy.

| Data | Rummyyyy |
| --- | --- |
| Tweets downloaded | 1420 |
| Retweets | 156 |
| Short tweets | 139 |
| Tweets kept | 1125 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/5frannca/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 @926stories's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1dvniaka) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1dvniaka/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/926stories')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/nasa/1634620756871/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

NASA

@nasa

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 NASA.

| Data | NASA |
| --- | --- |
| Tweets downloaded | 3250 |
| Retweets | 791 |
| Short tweets | 128 |
| Tweets kept | 2331 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2d5v4ryv/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 @nasa's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/24dhsaf3) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/24dhsaf3/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/nasa')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/sharsenko/1626797315466/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Willo

@sharsenko

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 Willo.

| Data | Willo |
| --- | --- |
| Tweets downloaded | 1279 |
| Retweets | 304 |
| Short tweets | 219 |
| Tweets kept | 756 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1r0bziin/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 @sharsenko's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/37iziw4p) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/37iziw4p/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/sharsenko')
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)


---
language: en
thumbnail: http://www.huggingtweets.com/badbunnytwitch/1643762099951/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

BadBunny 💢

@badbunnytwitch

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 BadBunny 💢.

| Data | BadBunny 💢 |
| --- | --- |
| Tweets downloaded | 3246 |
| Retweets | 177 |
| Short tweets | 1018 |
| Tweets kept | 2051 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/jrtmk7ym/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 @badbunnytwitch's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/r2t5349l) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/r2t5349l/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/badbunnytwitch')
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)


---
language: en
thumbnail: https://github.com/borisdayma/huggingtweets/blob/master/img/logo.png?raw=true
tags:
- huggingtweets
widget:
- text: "My dream is"
---

eripsa 🤖 AI Bot

@eripsa bot

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 [@eripsa's tweets](https://twitter.com/eripsa).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3212 |
| Retweets | 1511 |
| Short tweets | 149 |
| Tweets kept | 1552 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/i4inmqrl/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 @eripsa's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2xn30w4y) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2xn30w4y/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/eripsa')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/lesterbuxton/1616785685686/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Lester Buxton 🤖 AI Bot

@lesterbuxton bot

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 [@lesterbuxton's tweets](https://twitter.com/lesterbuxton).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3237 |
| Retweets | 917 |
| Short tweets | 219 |
| Tweets kept | 2101 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3j18pvka/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 @lesterbuxton's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1euckzka) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1euckzka/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/lesterbuxton')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/kleocadiaa/1624475669314/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

ultraviolet, infrared

@kleocadiaa

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 ultraviolet, infrared.

| Data | ultraviolet, infrared |
| --- | --- |
| Tweets downloaded | 3214 |
| Retweets | 885 |
| Short tweets | 204 |
| Tweets kept | 2125 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3b61on17/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 @kleocadiaa's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/q1yb1nlj) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/q1yb1nlj/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/kleocadiaa')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/imjustuhgrl/1601318938681/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

<link rel="stylesheet" href="https://unpkg.com/@tailwindcss/typography@0.2.x/dist/typography.min.css">

Jaelynn 🤖 AI Bot

@imjustuhgrl bot

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://app.wandb.ai/wandb/huggingtweets/reports/HuggingTweets-Train-a-model-to-generate-tweets--VmlldzoxMTY5MjI).

## Training data

The model was trained on [@imjustuhgrl's tweets](https://twitter.com/imjustuhgrl).

Data
Quantity

Tweets downloaded
3236

Retweets
15

Short tweets
512

Tweets kept
2709

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/4phdk9xl/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 @imjustuhgrl's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/22432rm3) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/22432rm3/artifacts) is logged and versioned.

## Intended uses & limitations

### How to use

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/imjustuhgrl')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/iamdevloper/1634677176847/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

I Am Devloper

@iamdevloper

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 I Am Devloper.

| Data | I Am Devloper |
| --- | --- |
| Tweets downloaded | 3244 |
| Retweets | 190 |
| Short tweets | 233 |
| Tweets kept | 2821 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2k1120ro/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 @iamdevloper's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2wr63mia) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2wr63mia/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/iamdevloper')
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)


---
language: en
thumbnail: https://www.huggingtweets.com/playboicarti/1623642457997/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

💋🧛🏿♀

@playboicarti

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 💋🧛🏿♀.

| Data | 💋🧛🏿♀ |
| --- | --- |
| Tweets downloaded | 3110 |
| Retweets | 567 |
| Short tweets | 627 |
| Tweets kept | 1916 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2760nf9v/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 @playboicarti's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/leodsru6) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/leodsru6/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/playboicarti')
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)