Update app.py
Browse files
app.py
CHANGED
@@ -109,7 +109,6 @@ tokenizer1 = AutoTokenizer.from_pretrained("AlGe/deberta-v3-large_Int_segment",
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model2 = AutoModelForSequenceClassification.from_pretrained("AlGe/deberta-v3-large_seq_ext", num_labels=1, token=auth_token)
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@spaces.GPU
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# Define functions to process inputs
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def process_ner(text, pipeline):
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output = pipeline(text)
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@@ -150,7 +149,8 @@ def process_classification(text, model1, model2, tokenizer1):
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score = prediction1 / (prediction2 + prediction1)
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return f"{round(prediction1, 1)}", f"{round(prediction2, 1)}", f"{round(score, 2)}"
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def all(text):
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return process_ner(text, pipe_bin), process_ner(text, pipe_ext), process_classification(text, model1, model2, tokenizer1)[0], process_classification(text, model1, model2, tokenizer1)[1], process_classification(text, model1, model2, tokenizer1)[2]
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model2 = AutoModelForSequenceClassification.from_pretrained("AlGe/deberta-v3-large_seq_ext", num_labels=1, token=auth_token)
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# Define functions to process inputs
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def process_ner(text, pipeline):
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output = pipeline(text)
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score = prediction1 / (prediction2 + prediction1)
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return f"{round(prediction1, 1)}", f"{round(prediction2, 1)}", f"{round(score, 2)}"
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@spaces.GPU
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def all(text):
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return process_ner(text, pipe_bin), process_ner(text, pipe_ext), process_classification(text, model1, model2, tokenizer1)[0], process_classification(text, model1, model2, tokenizer1)[1], process_classification(text, model1, model2, tokenizer1)[2]
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