---
language: en
thumbnail: https://www.huggingtweets.com/yukonbrandon/1617458018352/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Brandon Macdonald 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3249 |
| Retweets | 105 |
| Short tweets | 128 |
| Tweets kept | 3016 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/36sc6qhf/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 @yukonbrandon's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/8xctkx0v) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/8xctkx0v/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/yukonbrandon')
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/almostnora/1616897539959/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

N.O.R.A 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3230 |
| Retweets | 191 |
| Short tweets | 494 |
| Tweets kept | 2545 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3hy929cp/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 @almostnora's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3l9u4t5m) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3l9u4t5m/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/almostnora')
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/flightlessmilfs/1643422380331/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Ali ψ

@flightlessmilfs

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 Ali ψ.

| Data | Ali ψ |
| --- | --- |
| Tweets downloaded | 1815 |
| Retweets | 642 |
| Short tweets | 181 |
| Tweets kept | 992 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1yuw97j7/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 @flightlessmilfs's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/31esgsfh/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/flightlessmilfs')
generator("My dream is", num_return_sequences=5)
```

## Limitations and bias

The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).

In addition, the data present in the user's tweets further affects the text generated by the model.

## About

*Built by Boris Dayma*

[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)

For more details, visit the project repository.

[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)


---
language: en
thumbnail: http://res.cloudinary.com/huggingtweets/image/upload/v1599931790/mchammer.jpg
tags:
- huggingtweets
widget:
- text: "My dream is"
---

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

MC HAMMER 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3228

Retweets
1006

Short tweets
1084

Tweets kept
1138

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/7qehxuzo/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 @mchammer's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/cibgo2pn) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/cibgo2pn/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/mchammer')
generator("My dream is", num_return_sequences=5)

### Limitations and bias

The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).

In addition, the data present in the user's tweets further affects the text generated by the model.

## About

*Built by Boris Dayma*

[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/borisdayma)

For more details, visit the project repository.

[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)


---
language: en
thumbnail: https://www.huggingtweets.com/hypogolic/1618114859275/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

ᴊᴀᴋᴇ 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3240 |
| Retweets | 843 |
| Short tweets | 232 |
| Tweets kept | 2165 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/n67xr7jp/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 @hypogolic's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/uzjvv38k) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/uzjvv38k/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/hypogolic')
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/spookysimon1/1621369998182/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

spooky_simon

@spookysimon1

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 spooky_simon.

| Data | spooky_simon |
| --- | --- |
| Tweets downloaded | 3225 |
| Retweets | 128 |
| Short tweets | 954 |
| Tweets kept | 2143 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/jdigg9qt/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 @spookysimon1's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/e675ooeo) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/e675ooeo/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/spookysimon1')
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/sonyaism/1617756213982/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

sonya 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3243 |
| Retweets | 16 |
| Short tweets | 579 |
| Tweets kept | 2648 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2hujh3sc/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 @sonyaism's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/202umy6y) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/202umy6y/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/sonyaism')
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/kali_k_priv/1617893602566/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Kálí Kalváll 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3216 |
| Retweets | 309 |
| Short tweets | 218 |
| Tweets kept | 2689 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/zzm9a4dx/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 @kali_k_priv's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/15iz4s58) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/15iz4s58/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/kali_k_priv')
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/enexisgroep/1602236741204/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">

Enexis Groep 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
1145

Retweets
409

Short tweets
10

Tweets kept
726

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/z3mr8ber/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 @enexisgroep's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/1ti1orhu) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/1ti1orhu/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/enexisgroep')
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/islamphobiacow-praisegodbarbon/1627056382131/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Boston Psychology PhD & keyvan

@islamphobiacow-praisegodbarbon

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 Boston Psychology PhD & keyvan.

| Data | Boston Psychology PhD | keyvan |
| --- | --- | --- |
| Tweets downloaded | 3224 | 3242 |
| Retweets | 858 | 179 |
| Short tweets | 251 | 223 |
| Tweets kept | 2115 | 2840 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3egvdux4/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 @islamphobiacow-praisegodbarbon's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/34hmjrwi) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/34hmjrwi/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/islamphobiacow-praisegodbarbon')
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/vennesports/1614525364767/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

VENN ESPORTS 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 107 |
| Retweets | 16 |
| Short tweets | 22 |
| Tweets kept | 69 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2wx6lrcs/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 @vennesports's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1fch18xq) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1fch18xq/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/vennesports')
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/annieqqqqqq/1608310442616/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">

anya 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
559

Retweets
108

Short tweets
120

Tweets kept
331

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1s097d58/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 @annieqqqqqq's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/zr7lf2if) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/zr7lf2if/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/annieqqqqqq')
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/sopitas/1628802863178/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Sopitas

@sopitas

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 Sopitas.

| Data | Sopitas |
| --- | --- |
| Tweets downloaded | 3250 |
| Retweets | 57 |
| Short tweets | 41 |
| Tweets kept | 3152 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1gbazc6u/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 @sopitas's tweets.

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

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/16oyipwp/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/sopitas')
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/inmidonot/1616937673978/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Su Başak 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 344 |
| Retweets | 6 |
| Short tweets | 15 |
| Tweets kept | 323 |

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/12l0mm4t) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/12l0mm4t/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/inmidonot')
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/mr_bubblezzz/1627706719452/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Mr_Bubblez

@mr_bubblezzz

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 Mr_Bubblez.

| Data | Mr_Bubblez |
| --- | --- |
| Tweets downloaded | 387 |
| Retweets | 97 |
| Short tweets | 55 |
| Tweets kept | 235 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2abt71za/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 @mr_bubblezzz's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/28jx54ax) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/28jx54ax/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/mr_bubblezzz')
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/benchestnut/1626453250687/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Ben Chestnut

@benchestnut

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 Ben Chestnut.

| Data | Ben Chestnut |
| --- | --- |
| Tweets downloaded | 3229 |
| Retweets | 943 |
| Short tweets | 124 |
| Tweets kept | 2162 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/lyrugs4q/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 @benchestnut's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2u96gtbs) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2u96gtbs/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/benchestnut')
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/godslovepariah/1642565537762/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

LOVER//PARIAH

@godslovepariah

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 LOVER//PARIAH.

| Data | LOVER//PARIAH |
| --- | --- |
| Tweets downloaded | 525 |
| Retweets | 9 |
| Short tweets | 10 |
| Tweets kept | 506 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/6l5fj9xw/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 @godslovepariah's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3v0x5r1a) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3v0x5r1a/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/godslovepariah')
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/alisonselby_/1624473155604/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Alison Selby

@alisonselby_

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 Alison Selby.

| Data | Alison Selby |
| --- | --- |
| Tweets downloaded | 3218 |
| Retweets | 319 |
| Short tweets | 290 |
| Tweets kept | 2609 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2e6i4sab/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 @alisonselby_'s tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/9gpt8ktz) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/9gpt8ktz/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/alisonselby_')
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/goon_lagoon__/1617849869460/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Goon 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 2654 |
| Retweets | 1390 |
| Short tweets | 186 |
| Tweets kept | 1078 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/11if3arq/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 @goon_lagoon__'s tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1fzipcm4) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1fzipcm4/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/goon_lagoon__')
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/comradekatebush/1619214883291/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

pollyamosrous 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3196 |
| Retweets | 238 |
| Short tweets | 564 |
| Tweets kept | 2394 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/113j7mcs/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 @comradekatebush's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1fy72axl) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1fy72axl/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/comradekatebush')
generator("My dream is", num_return_sequences=5)
```

## Limitations and bias

The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).

In addition, the data present in the user's tweets further affects the text generated by the model.

## About

*Built by Boris Dayma*

[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)

For more details, visit the project repository.

[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)


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

🤖 AI BOT 🤖

bill wurtz

@billwurtz

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 bill wurtz.

| Data | bill wurtz |
| --- | --- |
| Tweets downloaded | 3097 |
| Retweets | 29 |
| Short tweets | 97 |
| Tweets kept | 2971 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/dp3b69xq/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 @billwurtz's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/26fxeouc) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/26fxeouc/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/billwurtz')
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/sarahksilverman/1632239411653/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Sarah Silverman

@sarahksilverman

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 Sarah Silverman.

| Data | Sarah Silverman |
| --- | --- |
| Tweets downloaded | 3234 |
| Retweets | 1210 |
| Short tweets | 418 |
| Tweets kept | 1606 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/ujf2xx2x/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 @sarahksilverman's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/gxxv62fg) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/gxxv62fg/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/sarahksilverman')
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/boogie2988/1622323494391/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

boogie2988 😭🤡

@boogie2988

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 boogie2988 😭🤡.

| Data | boogie2988 😭🤡 |
| --- | --- |
| Tweets downloaded | 3242 |
| Retweets | 216 |
| Short tweets | 392 |
| Tweets kept | 2634 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/30jummgi/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 @boogie2988's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/38yren3o) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/38yren3o/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/boogie2988')
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/marxhaunting/1625868274804/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Karl Marx

@marxhaunting

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 Karl Marx.

| Data | Karl Marx |
| --- | --- |
| Tweets downloaded | 1287 |
| Retweets | 16 |
| Short tweets | 25 |
| Tweets kept | 1246 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1zcjng5j/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 @marxhaunting's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1nimlh0s) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1nimlh0s/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/marxhaunting')
generator("My dream is", num_return_sequences=5)
```

## Limitations and bias

The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).

In addition, the data present in the user's tweets further affects the text generated by the model.

## About

*Built by Boris Dayma*

[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)

For more details, visit the project repository.

[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)


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

🤖 AI BOT 🤖

𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹

@abnuo113

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 𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹.

| Data | 𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹𒐹 |
| --- | --- |
| Tweets downloaded | 3213 |
| Retweets | 316 |
| Short tweets | 1545 |
| Tweets kept | 1352 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/7huohook/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 @abnuo113's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2j8kmobh) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2j8kmobh/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/abnuo113')
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/opalresplendent/1617758418206/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Opal, Effortlessly 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3237 |
| Retweets | 406 |
| Short tweets | 499 |
| Tweets kept | 2332 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2e4yjxbc/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 @opalresplendent's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1x4wev2h) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1x4wev2h/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/opalresplendent')
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/island_iverson/1614113195211/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

nick casino 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3182 |
| Retweets | 367 |
| Short tweets | 193 |
| Tweets kept | 2622 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/dlr58v3e/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 @island_iverson's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/1vy3qci6) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/1vy3qci6/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/island_iverson')
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/saidemilyfrost/1616897949220/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

emily frost 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 397 |
| Retweets | 172 |
| Short tweets | 61 |
| Tweets kept | 164 |

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/204p5pw1) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/204p5pw1/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/saidemilyfrost')
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/atinux/1605286256394/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">

Sébastien Chopin 🤖 AI Bot

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

Data
Quantity

Tweets downloaded
3204

Retweets
792

Short tweets
302

Tweets kept
2110

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/6nzh2yez/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 @atinux's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/15g6ru92) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/15g6ru92/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/atinux')
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/dysexliaa/1616691912003/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

SoFine 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 1387 |
| Retweets | 205 |
| Short tweets | 224 |
| Tweets kept | 958 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/22uxy10l/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 @dysexliaa's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/28fr49gk) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/28fr49gk/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/dysexliaa')
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/deleteevelyn/1614106800270/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

evelyn 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3196 |
| Retweets | 277 |
| Short tweets | 358 |
| Tweets kept | 2561 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1cgctgf3/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 @deleteevelyn's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/inf2farl) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/inf2farl/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/deleteevelyn')
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/divorceenforcer/1614097005501/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

malignant tzara 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3148 |
| Retweets | 1127 |
| Short tweets | 574 |
| Tweets kept | 1447 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/2b3i6627/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 @divorceenforcer's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/13x1aewb) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/13x1aewb/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/divorceenforcer')
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/ciarandold/1614256896076/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Summoning Exodia at Charlie's 4 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3179 |
| Retweets | 675 |
| Short tweets | 199 |
| Tweets kept | 2305 |

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/11dwi7cz) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/11dwi7cz/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/ciarandold')
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/michelonfray4/1601451731753/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">

Michel Onfray 🤖 AI Bot

@michelonfray4 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 [@michelonfray4's tweets](https://twitter.com/michelonfray4).

Data
Quantity

Tweets downloaded
483

Retweets
222

Short tweets
88

Tweets kept
173

[Explore the data](https://app.wandb.ai/wandb/huggingtweets/runs/18u5girs/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 @michelonfray4's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://app.wandb.ai/wandb/huggingtweets/runs/19hut7nl) for full transparency and reproducibility.

At the end of training, [the final model](https://app.wandb.ai/wandb/huggingtweets/runs/19hut7nl/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/michelonfray4')
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/alexwadecraig/1616646989893/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Alexander Wade Craig 🤖 AI Bot

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

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 3220 |
| Retweets | 404 |
| Short tweets | 112 |
| Tweets kept | 2704 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3l824189/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 @alexwadecraig's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/3kat9k6l) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/3kat9k6l/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/alexwadecraig')
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/repkatieporter/1625156295007/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI BOT 🤖

Rep. Katie Porter

@repkatieporter

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 Rep. Katie Porter.

| Data | Rep. Katie Porter |
| --- | --- |
| Tweets downloaded | 2390 |
| Retweets | 81 |
| Short tweets | 28 |
| Tweets kept | 2281 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3m1ovwyo/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 @repkatieporter's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/26pjm1lq) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/26pjm1lq/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/repkatieporter')
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/goando-kenmcalinn-voluntas/1643509465268/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

🤖 AI CYBORG 🤖

Go Ando / PREDUCTS / THE GUILD & Ken McAlinn & V

@goando-kenmcalinn-voluntas

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 Go Ando / PREDUCTS / THE GUILD & Ken McAlinn & V.

| Data | Go Ando / PREDUCTS / THE GUILD | Ken McAlinn | V |
| --- | --- | --- | --- |
| Tweets downloaded | 3247 | 3250 | 3246 |
| Retweets | 91 | 22 | 1040 |
| Short tweets | 1680 | 2144 | 698 |
| Tweets kept | 1476 | 1084 | 1508 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/3kzei9u5/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 @goando-kenmcalinn-voluntas's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/2mdna8jc) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/2mdna8jc/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/goando-kenmcalinn-voluntas')
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/jasonchen0325/1616715271094/predictions.png
tags:
- huggingtweets
widget:
- text: "My dream is"
---

Jason Chen 🤖 AI Bot

@jasonchen0325 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 [@jasonchen0325's tweets](https://twitter.com/jasonchen0325).

| Data | Quantity |
| --- | --- |
| Tweets downloaded | 354 |
| Retweets | 30 |
| Short tweets | 9 |
| Tweets kept | 315 |

[Explore the data](https://wandb.ai/wandb/huggingtweets/runs/1wsqq8bl/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 @jasonchen0325's tweets.

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/w2gqjxjr) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/w2gqjxjr/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/jasonchen0325')
generator("My dream is", num_return_sequences=5)
```

## Limitations and bias

The model suffers from [the same limitations and bias as GPT-2](https://huggingface.co/gpt2#limitations-and-bias).

In addition, the data present in the user's tweets further affects the text generated by the model.

## About

*Built by Boris Dayma*

[![Follow](https://img.shields.io/twitter/follow/borisdayma?style=social)](https://twitter.com/intent/follow?screen_name=borisdayma)

For more details, visit the project repository.

[![GitHub stars](https://img.shields.io/github/stars/borisdayma/huggingtweets?style=social)](https://github.com/borisdayma/huggingtweets)


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

🤖 AI BOT 🤖

Mom

@behemilf

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 Mom.

| Data | Mom |
| --- | --- |
| Tweets downloaded | 3241 |
| Retweets | 858 |
| Short tweets | 346 |
| Tweets kept | 2037 |

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

Hyperparameters and metrics are recorded in the [W&B training run](https://wandb.ai/wandb/huggingtweets/runs/ss8n55dy) for full transparency and reproducibility.

At the end of training, [the final model](https://wandb.ai/wandb/huggingtweets/runs/ss8n55dy/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/behemilf')
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)