Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use jhgan/ko-sbert-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jhgan/ko-sbert-multitask with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jhgan/ko-sbert-multitask") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use jhgan/ko-sbert-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jhgan/ko-sbert-multitask") model = AutoModel.from_pretrained("jhgan/ko-sbert-multitask") - Inference
- Notebooks
- Google Colab
- Kaggle
[๋ผ์ด์ผ์ค ํ์ธ ์์ฒญ]
#4 opened 10 months ago
by
flipflop98
Adding `safetensors` variant of this model
#3 opened about 2 years ago
by
SFconvertbot
๋จ์ด์ฅ์ ์๋ก์ด ๋จ์ด๋ฅผ ๋ฃ๊ณ ์ ์ฉํ๋ ค๋ฉด ์ด๋ป๊ฒ ํด์ผ ํ๋์ง ์ ์ ์์๊น์?
2
#2 opened about 3 years ago
by
Gyeongmo