obladaet

Introduction

The HuggingArtists model, developed by Aleksey Korshuk, is a text generation model fine-tuned on the lyrics of the artist OBLADAET. It is built on top of the GPT-2 model and is designed to generate text in the style of OBLADAET's lyrics.

Architecture

The model uses the GPT-2 architecture, which is a transformer-based model known for its powerful text generation capabilities. It has been fine-tuned specifically on the OBLADAET lyrics dataset to adapt its language model to the style and themes present in the artist's music.

Training

The training process involved fine-tuning a pre-trained GPT-2 model using lyrics from OBLADAET. The dataset used for training is available on Hugging Face Datasets and can be accessed using the datasets library. During training, hyperparameters and metrics were tracked using Weights & Biases (W&B) to ensure transparency and reproducibility. The training data was logged as W&B artifacts at every step, and the final model was versioned for future use.

Guide: Running Locally

To use this model locally for text generation, follow these steps:

1. Install the Transformers Library:

   pip install transformers
   

2. Load the Model and Tokenizer:

   from transformers import AutoTokenizer, AutoModelWithLMHead
   
   tokenizer = AutoTokenizer.from_pretrained("huggingartists/obladaet")
   model = AutoModelWithLMHead.from_pretrained("huggingartists/obladaet")
   

3. Generate Text:

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

4. Consider Using Cloud GPUs:

   • If you require faster inference or need to handle larger workloads, consider using cloud GPU services such as AWS, GCP, or Azure.

License

The model, dataset, and associated code are subject to the limitations and biases inherent in the GPT-2 model. Users should be aware of the potential biases present in the training data and generated outputs. For full license details, refer to the project's repository on GitHub.