---
dataset_info:
  features:
  - name: input_ids
    sequence: int32
  - name: aa_seqs
    dtype: string
  splits:
  - name: train
    num_bytes: 61101706188
    num_examples: 9920628
  download_size: 5540646354
  dataset_size: 61101706188
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
10 million random examples from Uniref50 representative sequences (October 2023) and computed [selfies](https://github.com/aspuru-guzik-group/selfies) strings. The strings are stored as input ids from a custom selfies tokenizer. A BERT tokenizer with this vocabulary has been uploaded to this dataset under the files.

Intended for atom-wise protein language modeling.