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README.md
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---
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language: en
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license: mit
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tags:
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- GECToR_gotutiyan
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---
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# gector sample
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This is an unofficial pretrained model of GECToR ([Omelianchuk+ 2020](https://aclanthology.org/2020.bea-1.16/)).
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### How to use
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The code is avaliable from https://github.com/gotutiyan/gector.
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CLI
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```sh
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python predict.py --input <raw text file> --restore_dir gotutiyan/gector-roberta-base-5k --out <path to output file>
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```
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API
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```py
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from transformers import AutoTokenizer
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from gector.modeling import GECToR
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from gector.predict import predict, load_verb_dict
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import torch
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model_id = 'gotutiyan/gector-roberta-base-5k'
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model = GECToR.from_pretrained(model_id)
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if torch.cuda.is_available():
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model.cuda()
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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encode, decode = load_verb_dict('data/verb-form-vocab.txt')
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srcs = [
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'This is a correct sentence.',
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'This are a wrong sentences'
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]
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corrected = predict(
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model, tokenizer, srcs,
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encode, decode,
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keep_confidence=0.0,
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min_error_prob=0.0,
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n_iteration=5,
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batch_size=2,
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)
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print(corrected)
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```
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