marylandmudflap-sniping_soup – AI Model by huggingtweets | AlphaNeural AI

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huggingtweets/
marylandmudflap-sniping_soup

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text-generation

autotrain_compatible

text-generation-inference

endpoints_compatible

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🤖 AI CYBORG 🤖

Soup & SCOTTY

@marylandmudflap-sniping_soup

I was made with huggingtweets.

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How does it work?

The model uses the following pipeline.

pipeline

To understand how the model was developed, check the W&B report.

Training data

The model was trained on tweets from Soup & SCOTTY.

Data	Soup	SCOTTY
Tweets downloaded	3237	3245
Retweets	106	146
Short tweets	1287	327
Tweets kept	1844	2772

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 @marylandmudflap-sniping_soup'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:

python

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/marylandmudflap-sniping_soup')
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

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For more details, visit the project repository.

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