Create README.md
Browse files__Purpose__: classifies protein sequence into Thermophilic (> 60C) or Mesophilic (<40C) by host organism growth temperature.
__Training__:
ProteinBERT (Rostlab/prot_bert) was fine tuned on a class balanced version of learn2therm (see [here]()), about 250k protein amino acid sequences.
Training parameters below:
TODO
See the [training repository](https://github.com/BeckResearchLab/learn2thermML) for code.
__Usage__:
Prepare sequences identically to using the original pretrained model:
```
from transformers import BertModelForSequenceClassification, BertTokenizer
import torch
import re
tokenizer = BertTokenizer.from_pretrained("evankomp/learn2therm", do_lower_case=False )
model = BertModelForSequenceClassification.from_pretrained("evankomp/learn2therm")
sequence_Example = "A E T C Z A O"
sequence_Example = re.sub(r"[UZOB]", "X", sequence_Example)
encoded_input = tokenizer(sequence_Example, return_tensors='pt')
output = torch.argmax(model(**encoded_input), dim=1)
```
1 indicates thermophilic, 0 mesophilic.