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huggingartists / logic
Model's Last Updated: September 24 2021
text-generation
Introduction of logic
Model Details of logic
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 Logic.
Dataset is available here . And can be used with:
from datasets import load_dataset
dataset = load_dataset("huggingartists/logic")
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 Logic'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/logic')
generator("I am", num_return_sequences=5)
Or with Transformers library:
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("huggingartists/logic")
model = AutoModelWithLMHead.from_pretrained("huggingartists/logic")
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.
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More Information About logic huggingface.co Model
Url of logic
logic huggingface.co Url
Provider of logic huggingface.co
Other API from huggingartists
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