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huggingtweets/oframblers
oframblers is a text generation model from huggingtweets. Use it when you need the model to write or continue text. It is set up for transformers.
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Downloads · 30 days
13
2% of all-time downloads
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From the Hugging Face model README
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 @oframblers's tweets.
| Data | Quantity |
|---|---|
| Tweets downloaded | 2471 |
| Retweets | 75 |
| Short tweets | 352 |
| Tweets kept | 2044 |
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 @oframblers'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/oframblers')
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.