Sentence Similarity
sentence-transformers
PyTorch
Transformers
Korean
bert
feature-extraction
TAACO
text-embeddings-inference
Instructions to use KDHyun08/TAACO_STS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use KDHyun08/TAACO_STS with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KDHyun08/TAACO_STS") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Transformers
How to use KDHyun08/TAACO_STS with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("KDHyun08/TAACO_STS") model = AutoModel.from_pretrained("KDHyun08/TAACO_STS") - Notebooks
- Google Colab
- Kaggle
Upload with huggingface_hub
Browse files
README.md
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# TAACO_Similarity
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๋ณธ ๋ชจ๋ธ์ [Sentence-transformers](https://www.SBERT.net)๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ KLUE์ STS(Sentence Textual Similarity) ๋ฐ์ดํฐ์
์ ํตํด ํ๋ จ์ ์งํํ ๋ชจ๋ธ์
๋๋ค.
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ํ์๊ฐ ์ ์ํ๊ณ ์๋ ํ๊ตญ์ด ๋ฌธ์ฅ๊ฐ ๊ฒฐ์์ฑ ์ธก์ ๋๊ตฌ์ธ K-TAACO(๊ฐ์ )์ ์งํ ์ค ํ๋์ธ ๋ฌธ์ฅ ๊ฐ ์๋ฏธ์ ๊ฒฐ์์ฑ์ ์ธก์ ํ๊ธฐ ์ํด ์ ์ํ์์ต๋๋ค.
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๋ํ ๋ชจ๋์ ๋ง๋ญ์น์ ๋ฌธ์ฅ๊ฐ ์ ์ฌ๋ ๋ฐ์ดํฐ ๋ฑ ๋ค์ํ ๋ฐ์ดํฐ๋ฅผ ๊ตฌํด ์ถ๊ฐ ํ๋ จ์ ์งํํ ์์ ์
๋๋ค.
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## Usage (Sentence-Transformers)
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# TAACO_Similarity
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๋ณธ ๋ชจ๋ธ์ [Sentence-transformers](https://www.SBERT.net)๋ฅผ ๊ธฐ๋ฐ์ผ๋ก ํ๋ฉฐ KLUE์ STS(Sentence Textual Similarity) ๋ฐ์ดํฐ์
์ ํตํด ํ๋ จ์ ์งํํ ๋ชจ๋ธ์
๋๋ค.
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ํ์๊ฐ ์ ์ํ๊ณ ์๋ ํ๊ตญ์ด ๋ฌธ์ฅ๊ฐ ๊ฒฐ์์ฑ ์ธก์ ๋๊ตฌ์ธ K-TAACO(๊ฐ์ )์ ์งํ ์ค ํ๋์ธ ๋ฌธ์ฅ ๊ฐ ์๋ฏธ์ ๊ฒฐ์์ฑ์ ์ธก์ ํ๊ธฐ ์ํด ๋ณธ ๋ชจ๋ธ์ ์ ์ํ์์ต๋๋ค.
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๋ํ ๋ชจ๋์ ๋ง๋ญ์น์ ๋ฌธ์ฅ๊ฐ ์ ์ฌ๋ ๋ฐ์ดํฐ ๋ฑ ๋ค์ํ ๋ฐ์ดํฐ๋ฅผ ๊ตฌํด ์ถ๊ฐ ํ๋ จ์ ์งํํ ์์ ์
๋๋ค.
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## Usage (Sentence-Transformers)
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