---
license: apache-2.0
tags:
- pretrained
- modernbert
- protein
---

# Model Card for ModernBert-Prot-v1-34M (ModernBert for protein)

The ModernBert-Prot-v1-34M Large Language Model (LLM) is a pretrained generative DNA sequence model with 37M parameters. 
It is derived from ModernBERT model, which was simplified for DNA: the number of layers and the hidden size were reduced. 
The model was pretrained using 10M protein strings from the uniprot 50 database. 

## Load the model from huggingface:

```
import torch
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("RaphaelMourad/ModernBert-Prot-v1-34M", trust_remote_code=True) 
model = AutoModel.from_pretrained("RaphaelMourad/ModernBert-Prot-v1-34M", trust_remote_code=True)
```

## Calculate the embedding of a DNA sequence

```
insulin = "MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN"
inputs = tokenizer(insulin, return_tensors = 'pt')["input_ids"]
hidden_states = model(inputs)[0] # [1, sequence_length, 256]

# embedding with max pooling
embedding_max = torch.max(hidden_states[0], dim=0)[0]
print(embedding_max.shape) # expect to be 256
```

## Troubleshooting

Ensure you are utilizing a stable version of Transformers, 4.34.0 or newer.

## Notice

ModernBert-Prot-v1-34M is a pretrained base model for DNA.

## Contact
 
Raphaël Mourad. raphael.mourad@univ-tlse3.fr