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@@ -8,13 +8,19 @@ metrics:
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  - accuracy
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  pipeline_tag: text-classification
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  ---
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- # 0. Introduction
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  ---
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- # 1. Requirements
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  ```python
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  # my env
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  python==3.11.3
@@ -29,7 +35,7 @@ transformers>=4.0
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  ---
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- # 2. Load Model
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  ```python
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  from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
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  from transformers import TextClassificationPipeline
@@ -48,7 +54,7 @@ def load_bert():
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  ---
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- # 3. Use Model
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  ```python
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  import re
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  import sentiments
@@ -63,7 +69,7 @@ def predict_sentiment(text):
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  ---
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- # 4. sentiments.py
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  ```python
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  Feel = [
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  {"label": "๊ฐ€๋‚œํ•œ, ๋ถˆ์šฐํ•œ", "index": 0},
 
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  - accuracy
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  pipeline_tag: text-classification
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  ---
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+ # 1. Introduction
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+ ## 1.1 examples
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+ ![examples](https://github.com/BurningFalls/algorithm-study/assets/30232837/596e5010-53b6-4598-8dd3-4ef7fc65e60e)
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+
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+ ## 1.2 f1-score
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+
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+ ![bert_accuracy](https://github.com/BurningFalls/algorithm-study/assets/30232837/58830340-aebe-4dc2-85fa-313138ac3020)
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  ---
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+ # 2. Requirements
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  ```python
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  # my env
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  python==3.11.3
 
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  ---
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+ # 3. Load
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  ```python
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  from transformers import AutoTokenizer, TFAutoModelForSequenceClassification
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  from transformers import TextClassificationPipeline
 
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  ---
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+ # 4. Usage
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  ```python
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  import re
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  import sentiments
 
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  ---
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+ # 5. sentiments.py
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  ```python
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  Feel = [
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  {"label": "๊ฐ€๋‚œํ•œ, ๋ถˆ์šฐํ•œ", "index": 0},