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huggingtweets/
cj_johnson17th-lucawashenko-lukealexxander-roguewealth

Name: cj_johnson17th-lucawashenko-lukealexxander-roguewealth
Availability: InStock

text-generation-inference

endpoints_compatible

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🤖 AI CYBORG 🤖

Luca & ROGUEWEALTH & Luke Alexander & WealthSquad Chris

@cj_johnson17th-lucawashenko-lukealexxander-roguewealth

I was made with huggingtweets.

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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 Luca & ROGUEWEALTH & Luke Alexander & WealthSquad Chris.

Data	Luca	ROGUEWEALTH	Luke Alexander	WealthSquad Chris
Tweets downloaded	2324	3200	3240	3239
Retweets	54	23	279	329
Short tweets	141	711	699	583
Tweets kept	2129	2466	2262	2327

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 @cj_johnson17th-lucawashenko-lukealexxander-roguewealth'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/cj_johnson17th-lucawashenko-lukealexxander-roguewealth')
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.