added the readme

README.md

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+---
+annotations_creators:
+  - no-annotation
+language_creators:
+  - no-annotation
+task_categories:
+  - text-classification
+tags:
+  - genomics
+  - dna
+  - dnabert
+  - bioinformatics
+  - mouse-dna
+  - tokenized
+source_datasets:
+  - davidcechak/Mouse_DNA_v0
+language:
+  - en
+license: other
+license_name: unspecified
+---
+
+# `Mouse_DNA_v0_DNABert6tokenized`
+
+## Dataset Description
+
+The `davidcechak/Mouse_DNA_v0_DNABert6tokenized` is a processed version of the `davidcechak/Mouse_DNA_v0` dataset. It contains mouse DNA sequences that have been tokenized using a 6-mer approach, making it directly compatible with models like DNABert for classification and other downstream tasks.
+
+This dataset can be used for comparative genomic analysis when used in conjunction with other tokenized datasets, such as the human DNA tokenized dataset (`simecek/Human_DNA_v0_DNABert6tokenized`). This allows for the training of classifiers that can distinguish between mouse and other species' DNA, providing a valuable resource for cross-species machine learning tasks in bioinformatics.
+
+## Dataset Structure
+
+The dataset is available in the `parquet` format and is likely split into training and testing subsets, though this needs to be confirmed.
+
+### Data Fields
+
+The dataset likely 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 base `Mouse_DNA_v0` dataset likely consists of DNA sequences from the mouse reference genome (*Mus musculus*).
+
+### Preprocessing and Tokenization
+
+The raw sequences from the `Mouse_DNA_v0` dataset 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., mouse vs. human).
+*   **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 mouse DNA sequences, which can then be fine-tuned for more specific downstream tasks.
+
+## 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. For any public or commercial use, it is necessary to verify the terms with the author, David Cechak, on Hugging Face.
+
+## 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/Mouse_DNA_v0_DNABert6tokenized")
+
+# Access the training split
+train_dataset = dataset["train"]