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
CHANGED
|
@@ -35,7 +35,7 @@ print(embeddings)
|
|
| 35 |
|
| 36 |
|
| 37 |
## Usage (์ค์ ๋ฌธ์ฅ ๊ฐ ์ ์ฌ๋ ๋น๊ต)
|
| 38 |
-
[Sentence-transformers](https://www.SBERT.net) ๋ฅผ ์ค์นํ ํ ์๋ ๋ด์ฉ๊ณผ ๊ฐ์ด ๋ฌธ์ฅ ๊ฐ ์ ์ฌ๋๋ฅผ ๋น๊ตํ ์ ์์ต๋๋ค.
|
| 39 |
query ๋ณ์๋ ๋น๊ต ๊ธฐ์ค์ด ๋๋ ๋ฌธ์ฅ(Source Sentence)์ด๊ณ ๋น๊ต๋ฅผ ์งํํ ๋ฌธ์ฅ์ docs์ list ํ์์ผ๋ก ๊ตฌ์ฑํ์๋ฉด ๋ฉ๋๋ค.
|
| 40 |
|
| 41 |
```python
|
|
|
|
| 35 |
|
| 36 |
|
| 37 |
## Usage (์ค์ ๋ฌธ์ฅ ๊ฐ ์ ์ฌ๋ ๋น๊ต)
|
| 38 |
+
[Sentence-transformers](https://www.SBERT.net) ๋ฅผ ์ค์นํ ํ ์๋ ๋ด์ฉ๊ณผ ๊ฐ์ด ๋ฌธ์ฅ ๊ฐ ์ ์ฌ๋๋ฅผ ๋น๊ตํ ์ ์์ต๋๋ค.
|
| 39 |
query ๋ณ์๋ ๋น๊ต ๊ธฐ์ค์ด ๋๋ ๋ฌธ์ฅ(Source Sentence)์ด๊ณ ๋น๊ต๋ฅผ ์งํํ ๋ฌธ์ฅ์ docs์ list ํ์์ผ๋ก ๊ตฌ์ฑํ์๋ฉด ๋ฉ๋๋ค.
|
| 40 |
|
| 41 |
```python
|