huggingtweets/

liyrex_irl-mkleosb-vermontsmash

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 LNR | Liyrex & T1 | MkLeo & Vermont Smash Ultimate.

| Data | LNR | Liyrex | T1 | MkLeo | Vermont Smash Ultimate | | --- | --- | --- | --- | | Tweets downloaded | 3203 | 3238 | 205 | | Retweets | 1683 | 510 | 26 | | Short tweets | 277 | 428 | 14 | | Tweets kept | 1243 | 2300 | 165 |

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 @liyrex_irl-mkleosb-vermontsmash'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.