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huggingtweets / danellisscience
Model's Last Updated: May 22 2021
text-generation
Introduction of danellisscience
Model Details of danellisscience
Daniel Ellis 🤖 AI Bot
@danellisscience bot
I was made with huggingtweets .
Create your own bot based on your favorite user with the demo !
How does it work?
The model uses the following pipeline.
To understand how the model was developed, check the W&B report .
Training data
The model was trained on @danellisscience's tweets .
| Data | Quantity |
|---|---|
| Tweets downloaded | 532 |
| Retweets | 107 |
| Short tweets | 30 |
| Tweets kept | 395 |
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 @danellisscience'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.
Intended uses & limitations
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/danellisscience')
generator("My dream is", 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.
About
Built by Boris Dayma
Runs of huggingtweets danellisscience on huggingface.co
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More Information About danellisscience huggingface.co Model
Url of danellisscience
danellisscience huggingface.co Url
Provider of danellisscience huggingface.co
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