Create README.md

README.md

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+---
+annotations_creators:
+  - no-annotation
+language_creators:
+  - no-annotation
+task_categories:
+  - text-classification
+tags:
+  - genomics
+  - dna
+  - dnabert
+  - bioinformatics
+  - worm-dna
+  - tokenized
+source_datasets:
+  - C. elegans (Caenorhabditis elegans) reference genome (unconfirmed)
+language:
+  - en
+license: other
+license_name: unspecified
+---
+
+# `Worm_DNA_v0_DNABert6tokenized`
+
+## Dataset Description
+
+The `davidcechak/Worm_DNA_v0_DNABert6tokenized` is a dataset containing DNA sequences from the model organism *Caenorhabditis elegans* (a nematode worm), preprocessed for use with large language models (LLMs) in genomics.
+
+This dataset was tokenized into non-overlapping 6-mers (6-base pair sequences), which is a standard approach for applying transformer models like DNABert to genomic data. It is ready for direct use in comparative genomics tasks, such as building a classifier to distinguish between human and worm DNA when used in conjunction with a compatible human DNA dataset like `simecek/Human_DNA_v0_DNABert6tokenized`.
+
+## Dataset Structure
+
+The dataset is available in the `parquet` format and is split into training and testing subsets.
+
+### Data Fields
+
+The dataset includes the following fields:
+*   **tokens**: A list of integers representing the 6-mer token IDs.
+*   **text**: The original DNA sequence string, consisting of the nucleotides `A`, `T`, `C`, and `G`.
+
+## Dataset Creation
+
+### Data Source
+
+The raw DNA sequences are likely derived from the reference genome of *Caenorhabditis elegans*.
+
+### Preprocessing and Tokenization
+
+The raw sequences were processed using a 6-mer tokenization scheme:
+1.  **Splitting**: Original DNA sequences were split into non-overlapping 6-mer tokens.
+2.  **Mapping**: Each unique 6-mer was mapped to a unique integer ID to create a vocabulary.
+3.  **Encoding**: The tokenized sequences were then represented as a list of these integer IDs.
+
+## Intended Uses
+
+The dataset can be used for:
+*   **Comparative Genomics**: Comparing genomic features and training models to distinguish between species (e.g., human vs. worm).
+*   **Genomic Classification**: Training and evaluating machine learning models on tasks like species identification from DNA sequences.
+*   **LLM Pre-training**: Providing a corpus for pre-training large language models on worm DNA sequences, which can then be fine-tuned for more specific downstream tasks related to *C. elegans* genomics.
+
+## Limitations and Ethical Considerations
+
+*   **Unspecified Origin**: Without an official dataset card from the author, the precise origin and collection methodology of the sequences are unknown. This may impact reproducibility and potential biases.
+*   **Licensing**: The license is currently unspecified. Users should exercise caution and attempt to verify licensing terms with the author, David Cechak, before commercial or public use.
+
+## How to Get the Dataset
+
+You can easily load this dataset from the Hugging Face Hub using the `datasets` library:
+
+```python
+from datasets import load_dataset
+
+# Load the tokenized dataset
+dataset = load_dataset("davidcechak/Worm_DNA_v0_DNABert6tokenized")
+
+# Access the training split
+train_dataset = dataset["train"]