# BerTELEO

A bert model pre-trained on short DNA sequence the teleo marker from zhihan1996/DNABERT-2-117M
use this model for teleo sequence emmebdding

Paper not already release.

How use : 


```python

from transformers import AutoTokenizer, AutoModel, AutoModelForMaskedLM
import torch

model_id = "gustoudu81/BerTeleo"

tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModel.from_pretrained(model_id, trust_remote_code=True)

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model = model.to(device).eval()

inputs = tokenizer("ACGTACGTACGT", return_tensors="pt")
inputs = {k: v.to(device) for k, v in inputs.items()}

with torch.no_grad():
    hidden_states = model(**inputs)[0]


# embedding with mean pooling
embedding_mean = torch.mean(hidden_states[0], dim=0)
print(embedding_mean.shape) # expect to be 768

# embedding with max pooling
embedding_max = torch.max(hidden_states[0], dim=0)[0]
print(embedding_max.shape) # expect to be 768
```