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

juggalo kokopelli 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3178 |
| Retweets | 452 |
| Short tweets | 397 |
| Tweets kept | 2329 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/ghn4ya3z/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 @billtheponyfan's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/31cu6fzd) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/31cu6fzd/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/billtheponyfan')
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/ibaillanos/1641753367000/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Ibai

@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.

| Data | Ibai |
| --- | --- |
| Tweets downloaded | 3250 |
| Retweets | 28 |
| Short tweets | 669 |
| Tweets kept | 2553 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3qyv6lsf/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 @ibaillanos's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/cxnkmkg6) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/cxnkmkg6/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/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/_lukeharris/1602255697233/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">

Luke Harris 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
1232

Retweets
470

Short tweets
102

Tweets kept
660

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/2vhslate/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 @_lukeharris's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/3ae8jfk6) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/3ae8jfk6/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/_lukeharris')
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/discarddiscord/1614246710317/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

luna 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 1495 |
| Retweets | 289 |
| Short tweets | 213 |
| Tweets kept | 993 |

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2g2xt22m) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2g2xt22m/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/discarddiscord')
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/daltonegreene/1616643742816/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Hugh Jazz 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3237 |
| Retweets | 183 |
| Short tweets | 354 |
| Tweets kept | 2700 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/25ywih65/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 @daltonegreene's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2yizvyce/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/daltonegreene')
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/i_am_kirook/1614143839460/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Kirook 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3036 |
| Retweets | 2210 |
| Short tweets | 98 |
| Tweets kept | 728 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/eha93a65/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 @i_am_kirook's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1oalyp1r) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1oalyp1r/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/i_am_kirook')
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/vtubercringe/1620710616387/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Avatar of VTuber & Fan Cringe/Drama

@vtubercringe

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 Avatar of VTuber & Fan Cringe/Drama.

| Data | Avatar of VTuber & Fan Cringe/Drama |
| --- | --- |
| Tweets downloaded | 3244 |
| Retweets | 382 |
| Short tweets | 476 |
| Tweets kept | 2386 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2ul2c4ob/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 @vtubercringe's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/r2wf7l5n) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/r2wf7l5n/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/vtubercringe')
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/hirox246/1643615877827/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

ひろゆき, Hiroyuki Nishimura

@hirox246

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 ひろゆき, Hiroyuki Nishimura.

| Data | ひろゆき, Hiroyuki Nishimura |
| --- | --- |
| Tweets downloaded | 3249 |
| Retweets | 288 |
| Short tweets | 948 |
| Tweets kept | 2013 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/4t5qkwzs/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 @hirox246's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/33qnhg00) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/33qnhg00/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/hirox246')
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/joemamachungus/1616642338313/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

ᘻᓰᑢᕼᗩᘿᒪ. 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 2971 |
| Retweets | 1244 |
| Short tweets | 163 |
| Tweets kept | 1564 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2fkbp395/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 @joemamachungus's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3q6uv1gm) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3q6uv1gm/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/joemamachungus')
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/gaybats1999/1614135497450/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

alphonse⛓🦇🌹 🤖 AI Bot

@gaybats1999 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 [@gaybats1999's tweets](https://twitter.com/gaybats1999).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 2783 |
| Retweets | 999 |
| Short tweets | 225 |
| Tweets kept | 1559 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/39y8clnw/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 @gaybats1999's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2mzsqlq3) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2mzsqlq3/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/gaybats1999')
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/glacius_gaming/1609012743315/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">

Glacius 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3197

Retweets
352

Short tweets
851

Tweets kept
1994

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3udvez1f/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 @glacius_gaming's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1w01n2c4) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1w01n2c4/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/glacius_gaming')
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/alogins/1616706593981/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Arturs Logins 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 1609 |
| Retweets | 133 |
| Short tweets | 177 |
| Tweets kept | 1299 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1ic2ynnv/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 @alogins's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/anvz7gt2) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/anvz7gt2/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/alogins')
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/charlieykim/1610394629494/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">

Charlie Kim 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3231

Retweets
280

Short tweets
23

Tweets kept
2928

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1vuvnq2j) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1vuvnq2j/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/charlieykim')
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/bladeecity-robber0540/1626331680252/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Aim & Combat Ballerina

@bladeecity-robber0540

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 Aim & Combat Ballerina.

| Data | Aim | Combat Ballerina |
| --- | --- | --- |
| Tweets downloaded | 1604 | 671 |
| Retweets | 314 | 66 |
| Short tweets | 487 | 303 |
| Tweets kept | 803 | 302 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3uvtcfjv/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 @bladeecity-robber0540's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/36qst0l8) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/36qst0l8/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/bladeecity-robber0540')
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/princessarylin/1616771078275/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Arylin Rylee 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3232 |
| Retweets | 229 |
| Short tweets | 213 |
| Tweets kept | 2790 |

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/186z4240) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/186z4240/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/princessarylin')
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/a__spaceman/1614115779135/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

A Space Man 𓀏 𓍐𓍒𓌐𓋨𓐭 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3192 |
| Retweets | 271 |
| Short tweets | 623 |
| Tweets kept | 2298 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/13dzl8xq/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 @a__spaceman's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/37svkwhk/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/a__spaceman')
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/morganstanley/1607110195449/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">

Morgan Stanley 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3234

Retweets
106

Short tweets
1

Tweets kept
3127

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3mn5apem/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 @morganstanley's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1gcjvbjs/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/morganstanley')
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/temujin9/1616634181884/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Con of Khans 🤖 AI Bot

@temujin9 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 [@temujin9's tweets](https://twitter.com/temujin9).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3248 |
| Retweets | 129 |
| Short tweets | 337 |
| Tweets kept | 2782 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/10u59ms9/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 @temujin9's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/11ged6oy) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/11ged6oy/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/temujin9')
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/javorszky/1602234108282/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">

Gabor Javorszky 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3137

Retweets
2139

Short tweets
67

Tweets kept
931

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/1cyr2cuz/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 @javorszky's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/2sa503ur) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/2sa503ur/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/javorszky')
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/visionify/1624017350891/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Visionify

@visionify

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 Visionify.

| Data | Visionify |
| --- | --- |
| Tweets downloaded | 70 |
| Retweets | 8 |
| Short tweets | 1 |
| Tweets kept | 61 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2wilyf5z/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 @visionify's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3pu4qf1m) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3pu4qf1m/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/visionify')
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_mcneil/1613291396989/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Wanda Maximoff’s Gay Son 🤖 AI Bot

@neil_mcneil 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_mcneil's tweets](https://twitter.com/neil_mcneil).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3220 |
| Retweets | 611 |
| Short tweets | 587 |
| Tweets kept | 2022 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3jn8zko2/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_mcneil's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2f119pdq) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2f119pdq/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_mcneil')
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/aly__dixon-haleyosomething-svpino/1632660543535/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

haley o'shaughnessy & Santiago & Aly Dixon

@aly__dixon-haleyosomething-svpino

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 haley o'shaughnessy & Santiago & Aly Dixon.

| Data | haley o'shaughnessy | Santiago | Aly Dixon |
| --- | --- | --- | --- |
| Tweets downloaded | 3241 | 3250 | 3003 |
| Retweets | 430 | 7 | 426 |
| Short tweets | 460 | 316 | 195 |
| Tweets kept | 2351 | 2927 | 2382 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1mt8xsda/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 @aly__dixon-haleyosomething-svpino's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/31g4nsgq) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/31g4nsgq/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/aly__dixon-haleyosomething-svpino')
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/6bnwo-hotwifekatrina-qobetty/1629204510133/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

♠✨BNWO IS TODAY✨♠ & hotwifekatrina & BettyBoopQoS

@6bnwo-hotwifekatrina-qobetty

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 ♠✨BNWO IS TODAY✨♠ & hotwifekatrina & BettyBoopQoS.

| Data | ♠✨BNWO IS TODAY✨♠ | hotwifekatrina | BettyBoopQoS |
| --- | --- | --- | --- |
| Tweets downloaded | 1481 | 287 | 129 |
| Retweets | 394 | 48 | 2 |
| Short tweets | 83 | 56 | 10 |
| Tweets kept | 1004 | 183 | 117 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/364y0lce/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 @6bnwo-hotwifekatrina-qobetty's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/141s7hku) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/141s7hku/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/6bnwo-hotwifekatrina-qobetty')
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/ladygaga-lennykravitz-snoopdogg/1635473619575/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Lady Gaga & Lenny Kravitz & Snoop Dogg

@ladygaga-lennykravitz-snoopdogg

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 Lady Gaga & Lenny Kravitz & Snoop Dogg.

| Data | Lady Gaga | Lenny Kravitz | Snoop Dogg |
| --- | --- | --- | --- |
| Tweets downloaded | 3133 | 3068 | 3232 |
| Retweets | 627 | 133 | 622 |
| Short tweets | 304 | 293 | 944 |
| Tweets kept | 2202 | 2642 | 1666 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1scwkzam/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 @ladygaga-lennykravitz-snoopdogg's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/30u3gh5i) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/30u3gh5i/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/ladygaga-lennykravitz-snoopdogg')
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/kpnsecurity/1625581202096/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

KPN Security

@kpnsecurity

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 KPN Security.

| Data | KPN Security |
| --- | --- |
| Tweets downloaded | 507 |
| Retweets | 109 |
| Short tweets | 9 |
| Tweets kept | 389 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/34p5iycs/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 @kpnsecurity's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1r2x39u7) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1r2x39u7/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/kpnsecurity')
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/pbhushan1/1604318454256/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">

Prashant Bhushan 🤖 AI Bot

@pbhushan1 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 [@pbhushan1's tweets](https://twitter.com/pbhushan1).

Data
Quantity

Tweets downloaded
3206

Retweets
1532

Short tweets
31

Tweets kept
1643

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/203wsfx3/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 @pbhushan1's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/pvjmkq9e) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/pvjmkq9e/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/pbhushan1')
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/kartographien/1633624710455/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

👽 kart (ographien)

@kartographien

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 👽 kart (ographien).

| Data | 👽 kart (ographien) |
| --- | --- |
| Tweets downloaded | 1915 |
| Retweets | 115 |
| Short tweets | 74 |
| Tweets kept | 1726 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/wt43qgri/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 @kartographien's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/knaecetq/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/kartographien')
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/____devii/1614135668330/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Devii 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3084 |
| Retweets | 1521 |
| Short tweets | 288 |
| Tweets kept | 1275 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2ffmdq5y/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 @____devii's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3bjpt7k3) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3bjpt7k3/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/____devii')
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/dh7net/1602195754110/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">

Damien Henry 🤖 AI Bot

@dh7net 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 [@dh7net's tweets](https://twitter.com/dh7net).

Data
Quantity

Tweets downloaded
2463

Retweets
857

Short tweets
227

Tweets kept
1379

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/26i29me7/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 @dh7net's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/6w8xyhch) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/6w8xyhch/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/dh7net')
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/georgenotfound/1622013920235/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

George

@georgenotfound

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 George.

| Data | George |
| --- | --- |
| Tweets downloaded | 848 |
| Retweets | 6 |
| Short tweets | 310 |
| Tweets kept | 532 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2doc1coj/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 @georgenotfound's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/155sbgzb) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/155sbgzb/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/georgenotfound')
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/ica_csab/1609602488446/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">

Comm Sci 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
1867

Retweets
947

Short tweets
32

Tweets kept
888

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/qqqm6bwp/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 @ica_csab's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2oqp0es9) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2oqp0es9/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/ica_csab')
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/cochairmeshawn/1639363549909/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

meshawn maddock

@cochairmeshawn

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 meshawn maddock.

| Data | meshawn maddock |
| --- | --- |
| Tweets downloaded | 2909 |
| Retweets | 1334 |
| Short tweets | 267 |
| Tweets kept | 1308 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2gcrdu5h/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 @cochairmeshawn's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1pdiqrr1) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1pdiqrr1/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/cochairmeshawn')
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/cooperativa/1604184922075/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">

Cooperativa 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3234

Retweets
417

Short tweets
2

Tweets kept
2815

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/114yjete/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 @cooperativa's tweets.

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

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/1vwsyebc/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/cooperativa')
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/hey_ash21/1640924344980/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

ash 🫀

@hey_ash21

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 ash 🫀.

| Data | ash 🫀 |
| --- | --- |
| Tweets downloaded | 3242 |
| Retweets | 193 |
| Short tweets | 132 |
| Tweets kept | 2917 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2tujmcza/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 @hey_ash21's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3pwdhn6q) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3pwdhn6q/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/hey_ash21')
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/elonmusk-kanyewest/1635528546431/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Elon Musk & ye

@elonmusk-kanyewest

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 Elon Musk & ye.

| Data | Elon Musk | ye |
| --- | --- | --- |
| Tweets downloaded | 3249 | 1856 |
| Retweets | 185 | 186 |
| Short tweets | 853 | 573 |
| Tweets kept | 2211 | 1097 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3ceinvzc/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 @elonmusk-kanyewest's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/16csk8qn) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/16csk8qn/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/elonmusk-kanyewest')
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/thebabylonbee-theonion/1627517094487/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

The Onion & The Babylon Bee

@thebabylonbee-theonion

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 The Onion & The Babylon Bee.

| Data | The Onion | The Babylon Bee |
| --- | --- | --- |
| Tweets downloaded | 3250 | 3249 |
| Retweets | 8 | 243 |
| Short tweets | 13 | 15 |
| Tweets kept | 3229 | 2991 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2ueetvmn/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 @thebabylonbee-theonion's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1g46l1ro) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1g46l1ro/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/thebabylonbee-theonion')
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/beingandslime/1616648200015/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Evan (master saucier) 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3245 |
| Retweets | 55 |
| Short tweets | 473 |
| Tweets kept | 2717 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2hj6ebde/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 @beingandslime's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2vtowykv/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/beingandslime')
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/fucko_el/1600841976446/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">

Bivek 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
2841

Retweets
761

Short tweets
104

Tweets kept
1976

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/249ga3z7/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 @fucko_el's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/ut8q3ybx) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/ut8q3ybx/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/fucko_el')
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/maxwellacameron/1617251170563/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Maxwell A. Cameron 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 2969 |
| Retweets | 392 |
| Short tweets | 182 |
| Tweets kept | 2395 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2k670nnb/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 @maxwellacameron's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2hkatk9i) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2hkatk9i/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/maxwellacameron')
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)