BERT base for proteins
This is bidirectional transformer pretrained on amino-acid sequences of human proteins.
Example: Insulin (P01308)
MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN
The model was trained using the masked-language-modeling objective.
Intended uses
This model is primarily aimed at being fine-tuned on the following tasks:
- protein function
- molecule-to-gene-expression mapping
- cell targeting
How to use in your code
from transformers import BertTokenizerFast, BertModel
checkpoint = 'unikei/bert-base-proteins'
tokenizer = BertTokenizerFast.from_pretrained(checkpoint)
model = BertModel.from_pretrained(checkpoint)
example = 'MALWMRLLPLLALLALWGPDPAAAFVNQHLCGSHLVEALYLVCGERGFFYTPKTRREAEDLQVGQVELGGGPGAGSLQPLALEGSLQKRGIVEQCCTSICSLYQLENYCN'
tokens = tokenizer(example, return_tensors='pt')
predictions = model(**tokens)
- Downloads last month
- 36
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.