Sentence Similarity
sentence-transformers
Safetensors
Korean
qwen3_vl
multimodal
embedding
visual-document-retrieval
korean
matryoshka
Instructions to use whybe-choi/kovre with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use whybe-choi/kovre with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("whybe-choi/kovre") 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] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from whybe-choi/kovre: direct link, hf CLI and curl.
- Browser
- Download file 334 Bytes
-
https://huggingface.co/whybe-choi/kovre/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://whybe-choi/kovre/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/whybe-choi/kovre/resolve/main/config_sentence_transformers.json
334 Bytes
| { | |
| "__version__": { | |
| "pytorch": "2.11.0+cu130", | |
| "sentence_transformers": "5.5.1", | |
| "transformers": "5.5.4" | |
| }, | |
| "default_prompt_name": "default", | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "default": "Represent the user's input.", | |
| "document": "", | |
| "query": "" | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |