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huggingartists / 100-gecs
Model's Last Updated: December 22 2021
text-generation
Introduction of 100-gecs
Model Details of 100-gecs
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 100 gecs.
Dataset is available here . And can be used with:
from datasets import load_dataset
dataset = load_dataset("huggingartists/100-gecs")
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 100 gecs'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/100-gecs')
generator("I am", num_return_sequences=5)
Or with Transformers library:
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("huggingartists/100-gecs")
model = AutoModelWithLMHead.from_pretrained("huggingartists/100-gecs")
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 100-gecs on huggingface.co
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More Information About 100-gecs huggingface.co Model
Url of 100-gecs
100-gecs huggingface.co Url
Provider of 100-gecs huggingface.co
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