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huggingtweets/gpeyronnet huggingtweets/gpeyronnet
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2 team members Β· 274 models

How to use this model directly from the πŸ€—/transformers library:

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from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("huggingtweets/gpeyronnet") model = AutoModelWithLMHead.from_pretrained("huggingtweets/gpeyronnet")
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Guillaume Peyronnet πŸ€– AI Bot
@gpeyronnet 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 @gpeyronnet's tweets.

Data Quantity
Tweets downloaded 3212
Retweets 633
Short tweets 160
Tweets kept 2419

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 @gpeyronnet'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',
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.


Built by Boris Dayma


For more details, visit the project repository.

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