Sponsored by
Vmake Labs Video Enhancer
huggingtweets / chriscantino
Model's Last Updated: September 20 2022
text-generation
Introduction of chriscantino
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 tweets from cantino.eth.
| Data | cantino.eth |
|---|---|
| Tweets downloaded | 3250 |
| Retweets | 38 |
| Short tweets | 666 |
| Tweets kept | 2546 |
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 @chriscantino'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.
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/chriscantino')
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
For more details, visit the project repository.
Runs of huggingtweets chriscantino on huggingface.co
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More Information About chriscantino huggingface.co Model
Url of chriscantino
chriscantino huggingface.co Url
Provider of chriscantino huggingface.co
Other API from huggingtweets
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