🤖 AI CYBORG 🤖
Dr Kate Compton, Code Wizard & Ian Horswill & Liz Gerber
@elizgerber-galaxykate-ianhorswill

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 Dr Kate Compton, Code Wizard & Ian Horswill & Liz Gerber.

Data Dr Kate Compton, Code Wizard Ian Horswill Liz Gerber
Tweets downloaded 3242 179 1622
Retweets 607 35 545
Short tweets 214 6 34
Tweets kept 2421 138 1043

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 @elizgerber-galaxykate-ianhorswill'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/elizgerber-galaxykate-ianhorswill')
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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