Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
Transformers
Korean
roberta
feature-extraction
text-embeddings-inference
Instructions to use jhgan/ko-sroberta-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use jhgan/ko-sroberta-multitask with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jhgan/ko-sroberta-multitask") 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 jhgan/ko-sroberta-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jhgan/ko-sroberta-multitask") model = AutoModel.from_pretrained("jhgan/ko-sroberta-multitask") - Inference
- Notebooks
- Google Colab
- Kaggle
| epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman | |
| -1,-1,0.8477045280392909,0.8559956140722809,0.8370636752767797,0.8440079435411166,0.8370234533153658,0.8438439443425015,0.8241822253054464,0.8233260855548581 | |