
I was made with huggingtweets .
Create your own bot based on your favorite user with the demo !
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 Bitcoin News & ETH Zürich & Solana.
| Data | Bitcoin News | ETH Zürich | Solana |
|---|---|---|---|
| Tweets downloaded | 3249 | 3246 | 3217 |
| Retweets | 28 | 1023 | 1697 |
| Short tweets | 3 | 34 | 214 |
| Tweets kept | 3218 | 2189 | 1306 |
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 @btctn-eth-solana'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:
from transformers import pipeline
generator = pipeline('text-generation',
model='huggingtweets/btctn-eth-solana')
generator("My dream is", num_return_sequences=5)
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 Boris Dayma
For more details, visit the project repository.