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| import streamlit as st | |
| from transformers import AutoTokenizer | |
| from transformers import TFAUTOModelForSequenceClassification | |
| import tensorflow as tf | |
| tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased') | |
| model = TFAUTOModelForSequenceClassification.from_pretrained('./') | |
| text = st.text_area('Your StackOverFlow Question') | |
| def preprocess_predict(text): | |
| inputs = tokenizer.encode(text, | |
| add_special_tokens = True, | |
| padding='max_length', | |
| truncation=True, | |
| max_length=SEQ_LEN, | |
| return_token_type_ids=False, | |
| return_tensors = 'tf') | |
| preds = model.predict(imputs) | |
| probabilities = tf.nn.softmax(preds['logits']) | |
| class_preds = np.argmax(probabilities,axis=1) | |
| return class_preds | |
| if text =True | |
| out = preprocess_predict(text) | |
| st.json(out) | |