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 AutoModelForMaskedLM, AutoTokenizer

# Load model and tokenizer - requires trust_remote_code
model = AutoModelForMaskedLM.from_pretrained("vsubasri/joint-nt-esm2-transcript-coding-dna", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("vsubasri/joint-nt-esm2-transcript-coding-dna", trust_remote_code=True)

# 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.