Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Korean
roberta
feature-extraction
text-embeddings-inference
Instructions to use bespin-global/klue-sroberta-base-continue-learning-by-mnr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bespin-global/klue-sroberta-base-continue-learning-by-mnr with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bespin-global/klue-sroberta-base-continue-learning-by-mnr") 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 bespin-global/klue-sroberta-base-continue-learning-by-mnr with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("bespin-global/klue-sroberta-base-continue-learning-by-mnr") model = AutoModel.from_pretrained("bespin-global/klue-sroberta-base-continue-learning-by-mnr") - Inference
- Notebooks
- Google Colab
- Kaggle
Ctrl+K