How does it work?

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

Training data

The model was trained on lyrics from GSPD.

Dataset is available here. And can be used with:

from datasets import load_dataset

dataset = load_dataset("huggingartists/gspd")

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 GSPD's lyrics.

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='huggingartists/gspd')
generator("I am", num_return_sequences=5)

Or with Transformers library:

from transformers import AutoTokenizer, AutoModelWithLMHead
  
tokenizer = AutoTokenizer.from_pretrained("huggingartists/gspd")

model = AutoModelWithLMHead.from_pretrained("huggingartists/gspd")