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gigabrain/
cag

Name: cag
Rating: 2.5 (6 reviews)

text-generation-inference

endpoints_compatible

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Layah Heilpern & Dovey "Rug The Fiat" Wan & Irene Zhao

@doveywan-irenezhao_-layahheilpern

How does it work?

The model uses the following pipeline.

Training data

The model was trained on tweets from Layah Heilpern & Dovey "Rug The Fiat" Wan & Irene Zhao.

Data	Layah Heilpern	Dovey "Rug The Fiat" Wan	Irene Zhao
Tweets downloaded	3249	3247	1945
Retweets	115	310	223
Short tweets	1453	269	417
Tweets kept	1681	2668	1305

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 @doveywan-irenezhao_-layahheilpern'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/cag')
generator("In crypto, ", 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

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gigabrain/cag