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88751d6
Update app.py
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app.py
CHANGED
@@ -4,7 +4,6 @@ import shap
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import numpy as np
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import scipy as sp
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import torch
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import tensorflow as tf
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import transformers
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from transformers import pipeline
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from transformers import RobertaTokenizer, RobertaModel
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@@ -51,8 +50,8 @@ ner_pipe = pipeline("ner", model=ner_model, tokenizer=ner_tokenizer, aggregation
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def adr_predict(x):
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encoded_input = tokenizer(x, return_tensors='pt')
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output = model(**encoded_input)
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scores = output[0][0].detach()
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scores =
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shap_values = explainer([str(x).lower()])
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# # Find the index of the class you want as the default reference (e.g., 'label_1')
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import numpy as np
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import scipy as sp
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import torch
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import transformers
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from transformers import pipeline
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from transformers import RobertaTokenizer, RobertaModel
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def adr_predict(x):
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encoded_input = tokenizer(x, return_tensors='pt')
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output = model(**encoded_input)
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scores = output[0][0].detach()
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scores = torch.nn.functional.softmax(scores)
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shap_values = explainer([str(x).lower()])
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# # Find the index of the class you want as the default reference (e.g., 'label_1')
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