Update README.md
Browse files
README.md
CHANGED
@@ -21,7 +21,7 @@ widget:
|
|
21 |
|
22 |
## Model description
|
23 |
|
24 |
-
[cdsBERT](https://doi.org/10.1101/2023.09.15.558027) is pLM with a codon vocabulary that was seeded with [ProtBERT](https://huggingface.co/Rostlab/prot_bert_bfd) and trained with a novel vocabulary extension pipeline called MELD. cdsBERT offers a highly biologically relevant latent space with excellent EC number prediction surpassing ProtBERT.
|
25 |
|
26 |
## How to use
|
27 |
|
@@ -30,7 +30,7 @@ widget:
|
|
30 |
import re
|
31 |
import torch
|
32 |
import torch.nn.functional as F
|
33 |
-
from transformers import
|
34 |
|
35 |
model = BertModel.from_pretrained('lhallee/cdsBERT') # load model
|
36 |
tokenizer = BertTokenizer.from_pretrained('lhallee/cdsBERT') # load tokenizer
|
|
|
21 |
|
22 |
## Model description
|
23 |
|
24 |
+
[cdsBERT+](https://doi.org/10.1101/2023.09.15.558027) is pLM with a codon vocabulary that was seeded with [ProtBERT](https://huggingface.co/Rostlab/prot_bert_bfd) and trained with a novel vocabulary extension pipeline called MELD. cdsBERT+ offers a highly biologically relevant latent space with excellent EC number prediction surpassing ProtBERT.
|
25 |
|
26 |
## How to use
|
27 |
|
|
|
30 |
import re
|
31 |
import torch
|
32 |
import torch.nn.functional as F
|
33 |
+
from transformers import BertModel, BertTokenizer
|
34 |
|
35 |
model = BertModel.from_pretrained('lhallee/cdsBERT') # load model
|
36 |
tokenizer = BertTokenizer.from_pretrained('lhallee/cdsBERT') # load tokenizer
|