Layah Heilpern & Dovey "Rug The Fiat" Wan & Irene Zhao
@doveywan-irenezhao_-layahheilpern
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',
model='huggingtweets/cag')
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.
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