Sentence Similarity
sentence-transformers
Safetensors
Model2Vec
Korean
feature-extraction
static-embedding
korean
matryoshka
Instructions to use kekeappa/kor-static-embedding-64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use kekeappa/kor-static-embedding-64 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("kekeappa/kor-static-embedding-64") 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] - Model2Vec
How to use kekeappa/kor-static-embedding-64 with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("kekeappa/kor-static-embedding-64") - Notebooks
- Google Colab
- Kaggle
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.sentence_transformer.modules.static_embedding.StaticEmbedding" | |
| } | |
| ] |