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
- Xet hash:
- 8e3f17bcc5cc9c421d9cda83a8ee451199dc79aed47ce257dde9611650dda7c6
- Size of remote file:
- 741 MB
- SHA256:
- acb29ec9aa58f05568fa6e42b8621fa701fc8fd1873f1a4a5f9122b907596c66
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