
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 muneeb.btc & BrendanEich & Joseph Lubin.
| Data | muneeb.btc | BrendanEich | Joseph Lubin |
|---|---|---|---|
| Tweets downloaded | 3248 | 3244 | 3193 |
| Retweets | 261 | 711 | 1930 |
| Short tweets | 259 | 228 | 29 |
| Tweets kept | 2728 | 2305 | 1234 |
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 @brendaneich-ethereumjoseph-muneeb'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/brendaneich-ethereumjoseph-muneeb')
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.