cbdb
/

ClassicalChineseLetterClassification

Text Classification

SequenceClassification

Inference Endpoints

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cbdb commited on Dec 12, 2022

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1 Parent(s): 715b737

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@@ -96,14 +96,14 @@ pred_class_proba = predict_class(test_sen)
 print(f'The predicted probability for the {list(pred_class_proba.keys())[0]} class: {list(pred_class_proba.values())[0]}')
 print(f'The predicted probability for the {list(pred_class_proba.keys())[1]} class: {list(pred_class_proba.values())[1]}')
 ```
-<font color="IndianRed"> >>> </font> The predicted probability for the not-letter class: 0.002029061783105135
-<font color="IndianRed"> >>> </font> The predicted probability for the letter class: 0.9979709386825562
 ```python
 pred_class = idx2label[np.argmax(list(pred_class_proba.values()))]
 print(f'The predicted class is: {pred_class}')
 ```
-<font color="IndianRed"> >>> </font> The predicted class is: letter
 Author: Queenie Luo (queenieluo[at]g.harvard.edu)

 print(f'The predicted probability for the {list(pred_class_proba.keys())[0]} class: {list(pred_class_proba.values())[0]}')
 print(f'The predicted probability for the {list(pred_class_proba.keys())[1]} class: {list(pred_class_proba.values())[1]}')
 ```
+<font color="IndianRed"> Output: </font> The predicted probability for the not-letter class: 0.002029061783105135
+<font color="IndianRed"> Output: </font> The predicted probability for the letter class: 0.9979709386825562
 ```python
 pred_class = idx2label[np.argmax(list(pred_class_proba.values()))]
 print(f'The predicted class is: {pred_class}')
 ```
+<font color="IndianRed"> Output: </font> The predicted class is: letter
 Author: Queenie Luo (queenieluo[at]g.harvard.edu)