huggingtweets/

quotes_sticky

I was made with huggingtweets.

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The model uses the following pipeline.

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

The model was trained on tweets from Sticky Quotes.

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

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

You can use this model directly with a pipeline for text generation:

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.

For more details, visit the project repository.