初始化项目，由ModelHub XC社区提供模型

Model: SamilPwC-AXNode-GenAI/PwC-Embedding_expr
Source: Original Platform

README.md

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+---
+language:
+- ko
+license: apache-2.0
+tags:
+- sentence-transformers
+- sentence-similarity
+- transformers
+---
+
+## PwC-Embedding-expr
+
+We trained the **PwC-Embedding-expr** model on top of the [multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct) embedding model.  
+To enhance performance in Korean, we applied our curated augmentation to STS datasets and fine-tuned the E5 model using a carefully balanced ratio across datasets.
+
+> ⚠️ This is an experimental model and is under continuous development.
+
+### To-do
+- [x] MTEB Leaderboard  
+- [ ] Technical Report
+
+
+## MTEB
+PwC-Embedding_expr was evaluated on the Korean subset of MTEB.  
+A leaderboard link will be added once it is published.
+
+| Task             | PwC-Embedding_expr |
+|------------------|--------------------|
+| KLUE-STS         | 0.88               | 
+| KLUE-TC          | 0.73               |
+| Ko-StrategyQA    | 0.80               | 
+| KorSTS           | 0.84               | 
+| MIRACL-Reranking | 0.72               | 
+| MIRACL-Retrieval | 0.65               |
+| **Average**      | **0.77**           |
+
+
+## Model
+- Base Model: [intfloat/multilingual-e5-large-instruct](https://huggingface.co/intfloat/multilingual-e5-large-instruct)
+- Model Size: 0.56B
+- Embedding Dimension: 1024
+- Max Input Tokens: 514
+
+
+## Requirements
+It works with the dependencies included in the latest version of MTEB.
+
+
+## Citation
+
+TBD (technical report expected September 2025)