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unikei/bert-base-proteins
bert-base-proteins is a fill-mask model from unikei. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as bigscience-openrail-m.
This is bidirectional transformer pretrained on amino-acid sequences of human proteins.
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.safetensors344 MB · 100%
From the Hugging Face model README
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.
This model is primarily aimed at being fine-tuned on the following tasks:
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)