mit_csail – AI Model by huggingtweets | AlphaNeural AI

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huggingtweets/
mit_csail

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text-generation

autotrain_compatible

text-generation-inference

endpoints_compatible

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MIT CSAIL 🤖 AI Bot

@mit_csail 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.

pipeline

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

Training data

The model was trained on @mit_csail's tweets.

Data	Quantity
Tweets downloaded	3226
Retweets	105
Short tweets	44
Tweets kept	3077

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 @mit_csail'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/mit_csail')
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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