🚀 HuggingArtists Model - Boris Grebenshikov
A language model trained on the lyrics of Boris Grebenshikov, created with the huggingartists framework.
I was made with huggingartists.
Create your own bot based on your favorite artist with the demo!
🚀 Quick Start
💻 Usage Examples
Basic Usage
from transformers import pipeline
generator = pipeline('text-generation',
model='huggingartists/boris-grebenshikov')
generator("I am", num_return_sequences=5)
Advanced Usage
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("huggingartists/boris-grebenshikov")
model = AutoModelWithLMHead.from_pretrained("huggingartists/boris-grebenshikov")
✨ Features
This model is trained on the lyrics of Boris Grebenshikov, enabling it to generate text in a style similar to his songs. It can be used for various creative tasks such as songwriting inspiration.
📦 Installation
No specific installation steps are provided here. You can use the model directly in Python code as shown in the usage examples, provided you have the necessary libraries (transformers, datasets) installed.
📚 Documentation
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 Boris Grebenshikov.
Dataset is available here.
And can be used with:
from datasets import load_dataset
dataset = load_dataset("huggingartists/boris-grebenshikov")
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 Boris Grebenshikov'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.
🔧 Technical Details
The model uses a pre-trained GPT - 2 architecture and fine - tunes it on the lyrics dataset of Boris Grebenshikov. The training process is tracked using Weights & Biases to ensure transparency and reproducibility.
📄 License
No license information is provided in the original document.
⚠️ Important Note
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.
💡 Usage Tip
This model can be a great source of inspiration for songwriting. Try different input prompts to get diverse text outputs.
About
Built by Aleksey Korshuk
For more details, visit the project repository.
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Transformers