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--- |
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license: mit |
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--- |
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```python |
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from transformers import AutoTokenizer, AutoModelForTokenClassification, TokenClassificationPipeline |
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import re |
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pipeline = TokenClassificationPipeline( |
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model=AutoModelForTokenClassification.from_pretrained("virtual-human-chc/prot_bert_bfd_ss3"), |
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tokenizer=AutoTokenizer.from_pretrained("virtual-human-chc/prot_bert_bfd_ss3", skip_special_tokens=True), |
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device=0 |
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) |
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sequences_Example = ["M G A E E E D T A I L Y P F T I S G N D R N G N F T I N F K G T P N S T N N G C I G Y S Y N G D W E K I E W E G S C D G N G N L V V E V P M S K I P A G V T S G E I Q I W W H S G D L K M T D Y K A L E H H H H H H", |
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"M N K Y L F E L P Y E R S E P G W T I R S Y F D L M Y N E N R F L D A V E N I V N K E S Y I L D G I Y C N F P D M N S Y D E S E H F E G V E F A V G Y P P D E D D I V I V S E E T C F E Y V R L A C E K Y L Q L H P E D T E K V N K L L S K I P S A G H H H H H H"] |
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sequences_Example = [re.sub(r"[UZOB]", "X", sequence) for sequence in sequences_Example] |
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print(pipeline(sequences_Example)) |
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``` |
