Edit model card
🤖 AI CYBORG 🤖
Boston Psychology PhD & Claire
@claire_v0ltaire-praisegodbarbon

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 Boston Psychology PhD & Claire.

Data Boston Psychology PhD Claire
Tweets downloaded 3211 3237
Retweets 798 494
Short tweets 272 566
Tweets kept 2141 2177

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 @claire_v0ltaire-praisegodbarbon'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/claire_v0ltaire-praisegodbarbon')
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

For more details, visit the project repository.

GitHub stars

Downloads last month
3
Hosted inference API
Text Generation
Examples
Examples
This model can be loaded on the Inference API on-demand.