CoolFace
Modelpublic

huggingtweets/fredricksonra

sourceHugging Faceupdated 5y agoView on Hugging Face
0likes14downloads
Model Card

<div class="inline-flex flex-col" style="line-height: 1.5;"> <div class="flex"> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;https://pbs.twimg.com/profileimages/1421105879408066565/hBHx-Rvl400x400.jpg&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> <div style="display:none; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url(&#39;&#39;)"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">๐Ÿค– AI BOT ๐Ÿค–</div> <div style="text-align: center; font-size: 16px; font-weight: 800">Rica af, she/her ๐Ÿ—ฝ๐Ÿณ๏ธโ€๐ŸŒˆ</div> <div style="text-align: center; font-size: 14px;">@fredricksonra</div> </div>

I was made with huggingtweets.

Create your own bot based on your favorite user with the demo!

How does it work?

The model uses the following pipeline.

pipeline

To understand how the model was developed, check the W&B report.

Training data

The model was trained on tweets from Rica af, she/her ๐Ÿ—ฝ๐Ÿณ๏ธโ€๐ŸŒˆ.

DataRica af, she/her ๐Ÿ—ฝ๐Ÿณ๏ธโ€๐ŸŒˆ
Tweets downloaded3208
Retweets2893
Short tweets47
Tweets kept268

Explore the data, which is tracked with W&B artifacts at every step of the pipeline.

Training procedure

The model is based on a pre-trained GPT-2 which is fine-tuned on @fredricksonra's tweets.

Hyperparameters and metrics are recorded in the W&B training run for full transparency and reproducibility.

At the end of training, the final model 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/fredricksonra')
generator("My dream is", num_return_sequences=5)

Limitations and bias

The model suffers from the same limitations and bias as GPT-2.

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://twitter.com/intent/follow?screen_name=borisdayma)

For more details, visit the project repository.

![GitHub stars](https://github.com/borisdayma/huggingtweets)