Sentence Similarity
sentence-transformers
PyTorch
Safetensors
Transformers
Korean
deberta-v2
feature-extraction
text-embeddings-inference
Instructions to use upskyy/kf-deberta-multitask with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use upskyy/kf-deberta-multitask with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("upskyy/kf-deberta-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 upskyy/kf-deberta-multitask with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("upskyy/kf-deberta-multitask") model = AutoModel.from_pretrained("upskyy/kf-deberta-multitask") - Notebooks
- Google Colab
- Kaggle
| epoch,steps,cosine_pearson,cosine_spearman,euclidean_pearson,euclidean_spearman,manhattan_pearson,manhattan_spearman,dot_pearson,dot_spearman | |
| -1,-1,0.8574826210027622,0.8625167208630782,0.8478939146405619,0.8524540783146085,0.8480117776348778,0.8527497844953591,0.8293372739387574,0.8286020232145503 | |