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Update app.py
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app.py
CHANGED
@@ -4,12 +4,12 @@ import pandas as pd
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import torch
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import numpy as np
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import re
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from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
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from transformers import AutoTokenizer, AutoModelForSequenceClassification,AdamW
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tokenizer = AutoTokenizer.from_pretrained('hackathon-pln-es/twitter_sexismo-finetuned-exist2021
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model = AutoModelForSequenceClassification.from_pretrained("hackathon-pln-es/twitter_sexismo-finetuned-exist2021
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import torch
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if torch.cuda.is_available():
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@@ -119,7 +119,8 @@ def run():
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tweet_list = [i.text for i in tweets]
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#tweet_list = [strip_undesired_chars(i.text) for i in tweets]
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text= pd.DataFrame(tweet_list)
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text[0] = text[0].apply(preprocess)
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text1=text[0].values
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indices1=tokenizer.batch_encode_plus(text1.tolist(),
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max_length=128,
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import torch
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import numpy as np
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import re
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from pysentimiento.preprocessing import preprocess_tweet
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from torch.utils.data import TensorDataset, DataLoader, RandomSampler, SequentialSampler
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from transformers import AutoTokenizer, AutoModelForSequenceClassification,AdamW
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tokenizer = AutoTokenizer.from_pretrained('hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021')
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model = AutoModelForSequenceClassification.from_pretrained("hackathon-pln-es/twitter_sexismo-finetuned-robertuito-exist2021")
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import torch
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if torch.cuda.is_available():
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tweet_list = [i.text for i in tweets]
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#tweet_list = [strip_undesired_chars(i.text) for i in tweets]
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text= pd.DataFrame(tweet_list)
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#text[0] = text[0].apply(preprocess)
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text[0] = text[0].apply(preprocess_tweet)
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text1=text[0].values
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indices1=tokenizer.batch_encode_plus(text1.tolist(),
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max_length=128,
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