Ot Rus

🚀 HuggingArtists Model - O.T (RUS)

This is a HuggingArtists model based on O.T (RUS). It can generate lyrics similar to O.T (RUS)'s style. You can create your own bot using this model and the provided demo.

🚀 Quick Start

You can use this model directly with a pipeline for text generation:

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingartists/ot-rus')
generator("I am", num_return_sequences=5)

Or with Transformers library:

from transformers import AutoTokenizer, AutoModelWithLMHead
  
tokenizer = AutoTokenizer.from_pretrained("huggingartists/ot-rus")

model = AutoModelWithLMHead.from_pretrained("huggingartists/ot-rus")

✨ Features

• Artist - Specific Generation: Generate lyrics in the style of O.T (RUS).
• Easy - to - Use: Can be used with simple Python code.

📦 Installation

No specific installation steps are provided in the original document. But you need to have the transformers and datasets libraries installed to use the model. You can install them using pip:

pip install transformers datasets

💻 Usage Examples

Basic Usage

from transformers import pipeline
generator = pipeline('text-generation',
                     model='huggingartists/ot-rus')
generator("I am", num_return_sequences=5)

📚 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 O.T (RUS). Dataset is available here. And can be used with:

from datasets import load_dataset

dataset = load_dataset("huggingartists/ot-rus")

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 O.T (RUS)'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 the pre - trained GPT - 2 architecture and fine - tunes it on O.T (RUS)'s lyrics. The training process is tracked using Weights & Biases to ensure transparency and reproducibility.

📄 License

No license information is provided in the original document.

Limitations and bias

⚠️ 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.

About

Built by Aleksey Korshuk

[](https://t.me/joinchat/_CQ04KjcJ - 4yZTky)

For more details, visit the project repository.