--- language: - en tags: - NLP license: mit datasets: - TristanBehrens/bach_garland_2024-100K base_model: None --- # Bach Garland Pharia - A Pharia model trained on Johann Sebastian Bach Style music Say Hello on [LinkedIn](https://www.linkedin.com/dr-tristan-behrens-734967a2/) and [X](https://x.com/DrTBehrens). ![Cover](bachgarlandpharia.jpg) This is a Pharia model trained on music by Johann Sebastian Bach. It includes all pieces of Bach's music that can be played on church organ. The samples come in the prototypical Garland notation. The dataset contains 100K samples and comes with a total token count of 144M. ## How to use 1. Clone this repository and follow the installation instructions: https://github.com/AI-Guru/helibrunna/ 2. Open and run the notebook `examples/music.ipynb`. Do not forget to add the id of this model. 3. Enjoy! ## Training ![Trained with Helibrunna](banner.jpg) Trained with [Helibrunna](https://github.com/AI-Guru/helibrunna) by [Dr. Tristan Behrens](https://de.linkedin.com/dr-tristan-behrens-734967a2). ## Configuration ``` training: model_name: bach_garland_pharia batch_size: 40 lr: 0.001 lr_warmup_steps: 1000 lr_decay_until_steps: 10000 lr_decay_factor: 0.001 weight_decay: 0.1 amp_precision: bfloat16 weight_precision: float32 enable_mixed_precision: true num_epochs: 8 output_dir: output/bach_garland_pharia save_every_step: 500 log_every_step: 10 wandb_project: bach_garland torch_compile: false model: type: pharia attention_bias: true attention_dropout: 0.0 eos_token_id: 0 bos_token_id: 127179 pad_token_id: 1 hidden_act: gelu hidden_size: 64 initializer_range: 0.02 intermediate_size: 128 max_position_embeddings: 2048 mlp_bias: true num_attention_heads: 4 num_hidden_layers: 4 num_key_value_heads: 4 rope_scaling: null rope_theta: 1000000 tie_word_embeddings: false use_cache: true context_length: 2048 vocab_size: 178 dataset: hugging_face_id: TristanBehrens/bach_garland_2024-100K tokenizer: type: whitespace fill_token: '[EOS]' ```