huggingtweets

<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('https://pbs.twimg.com/profile_images/1204851321481809920/T8QkUTSd_400x400.jpg')"> </div> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1606551197267140609/eOljGCkl_400x400.jpg')"> </div> <div style="display:inherit; margin-left: 4px; margin-right: 4px; width: 92px; height:92px; border-radius: 50%; background-size: cover; background-image: url('https://pbs.twimg.com/profile_images/1526705076575911936/xyoBxZ2l_400x400.jpg')"> </div> </div> <div style="text-align: center; margin-top: 3px; font-size: 16px; font-weight: 800">πŸ€– AI CYBORG πŸ€–</div> <div style="text-align: center; font-size: 16px; font-weight: 800">𝕸ΛYΛ𝑔𝒾𝓇𝓁 #𝟣 & HVND SIRSU & David Kolbusz</div> <div style="text-align: center; font-size: 14px;">@davidkolbusz-pristyles-sirsuhayb</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 𝕸ΛYΛ𝑔𝒾𝓇𝓁 #𝟣 & HVND SIRSU & David Kolbusz.

Data 𝕸ΛYΛ𝑔𝒾𝓇𝓁 #𝟣 HVND SIRSU David Kolbusz
Tweets downloaded 3118 3104 3240
Retweets 77 707 304
Short tweets 344 320 336
Tweets kept 2697 2077 2600

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 @davidkolbusz-pristyles-sirsuhayb'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:

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

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For more details, visit the project repository.

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