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NT DNA Model

This is the DNA component of a jointly trained NT-ESM2 model pair for DNA-protein analysis.

Model Details

  • Model Type: Nucleotide Transformer (NT) for DNA sequences
  • Training: Jointly trained with ESM2 protein model
  • Architecture: Transformer-based language model for DNA

Usage

from transformers import AutoModel, AutoTokenizer

# Load model and tokenizer
model = AutoModel.from_pretrained("vsubasri/joint-nt-esm2-transcript-coding-dna")
tokenizer = AutoTokenizer.from_pretrained("vsubasri/joint-nt-esm2-transcript-coding-dna")

# Example usage
dna_sequence = "ATCGATCGATCG"
inputs = tokenizer(dna_sequence, return_tensors="pt")
outputs = model(**inputs)

Training Details

  • Jointly trained with protein sequences for cross-modal understanding
  • Batch size: 8 (based on directory name)
  • Context length: 4096 tokens
  • Transcript-specific coding sequences

Files

  • config.json: Model configuration
  • model.safetensors: Model weights
  • tokenizer_config.json: Tokenizer configuration
  • vocab.txt: Vocabulary file
  • special_tokens_map.json: Special tokens mapping

Citation

If you use this model, please cite the original NT paper and your joint training work.