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Update README.md

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@@ -5,7 +5,7 @@ Korean Pre-Trained Crypto DeBERTa model fine-tuned on BTC sentiment classificati
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  For more details, check our work [CBITS: Crypto BERT Incorporated Trading System](https://ieeexplore.ieee.org/document/10014986) on IEEE Access.
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- ## Example Use Case: BTC Sentiment Classification
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  ```python
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  from transformers import AutoModelForSequenceClassification, AlbertTokenizer
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@@ -30,7 +30,7 @@ with torch.no_grad():
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  print("호재: {:.2f}% | 악재: {:.2f}% | 중립: {:.2f}%".format(output[0]*100,output[1]*100,output[2]*100))
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  ```
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- ## Example Use Case: Crypto Embedding Similarity
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  ```python
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  from transformers import AutoModelForSequenceClassification, AlbertTokenizer
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  from scipy.spatial.distance import cdist
 
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  For more details, check our work [CBITS: Crypto BERT Incorporated Trading System](https://ieeexplore.ieee.org/document/10014986) on IEEE Access.
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+ ## Example Use Case: Crypto News BTC Sentiment Classification
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  ```python
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  from transformers import AutoModelForSequenceClassification, AlbertTokenizer
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  print("호재: {:.2f}% | 악재: {:.2f}% | 중립: {:.2f}%".format(output[0]*100,output[1]*100,output[2]*100))
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  ```
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+ ## Example Use Case: Crypto News Embedding Similarity
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  ```python
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  from transformers import AutoModelForSequenceClassification, AlbertTokenizer
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  from scipy.spatial.distance import cdist