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README.md
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- **Base Model:** RoBERTa transformer architecture
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- **Tokenizer:** Custom K-mer Tokenizer with k-mer length of 6 and overlapping tokens
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- **Training:** Trained on a diverse dataset of 220 million 400bp fragments from 18k genomes (Bacteria and Archaea))
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- **Embeddings:** Generates sequence embeddings using mean pooling of hidden states
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**Steps to Use the Model:**
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- **Base Model:** RoBERTa transformer architecture
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- **Tokenizer:** Custom K-mer Tokenizer with k-mer length of 6 and overlapping tokens
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- **Training:** Trained on a diverse dataset of 220 million 400bp fragments from 18k genomes (Bacteria and Archaea))
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**Steps to Use the Model:**
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