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Layah Heilpern & Dovey "Rug The Fiat" Wan & Irene Zhao

How does it work?

The model uses the following pipeline.


Training data

The model was trained on tweets from Layah Heilpern & Dovey "Rug The Fiat" Wan & Irene Zhao.

Data Layah Heilpern Dovey "Rug The Fiat" Wan Irene Zhao
Tweets downloaded 3249 3247 1945
Retweets 115 310 223
Short tweets 1453 269 417
Tweets kept 1681 2668 1305

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 @doveywan-irenezhao_-layahheilpern'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',
generator("In crypto, ", 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.


Built by Gigabrain

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This model can be loaded on the Inference API on-demand.