huggingtweets/aimbotaimy-demi_naga-livingscribe

🤖 AI CYBORG 🤖

AimbotAimy 🍞🔞 NSFW V-Tuber & Poe's Law 🇷🇺: 3.33 You can (not) redo & Demi 'ドヤ顔' Naga

@aimbotaimy-demi_naga-livingscribe

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 tweets from AimbotAimy 🍞🔞 NSFW V-Tuber & Poe's Law 🇷🇺: 3.33 You can (not) redo & Demi 'ドヤ顔' Naga.

Data	AimbotAimy 🍞🔞 NSFW V-Tuber	Poe's Law 🇷🇺: 3.33 You can (not) redo	Demi 'ドヤ顔' Naga
Tweets downloaded	497	3242	3234
Retweets	60	433	909
Short tweets	125	564	341
Tweets kept	312	2245	1984

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 @aimbotaimy-demi_naga-livingscribe'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:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingtweets/aimbotaimy-demi_naga-livingscribe')
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.