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huggingartists / aaron-watson
Model's Last Updated: September 10 2021
text-generation
Introduction of aaron-watson
Model Details of aaron-watson
I was made with huggingartists .
Create your own bot based on your favorite artist with the demo !
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 Aaron Watson.
Dataset is available here . And can be used with:
from datasets import load_dataset
dataset = load_dataset("huggingartists/aaron-watson")
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 Aaron Watson'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/aaron-watson')
generator("I am", num_return_sequences=5)
Or with Transformers library:
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("huggingartists/aaron-watson")
model = AutoModelWithLMHead.from_pretrained("huggingartists/aaron-watson")
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 Aleksey Korshuk
For more details, visit the project repository.
Runs of huggingartists aaron-watson on huggingface.co
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More Information About aaron-watson huggingface.co Model
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