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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7863689c827ad793d98692998e3ebd35762d7330d2c543ee6159c6a2fe6ffd7d
- Size of remote file:
- 741 MB
- SHA256:
- 3390b04cd5ca99e759732e19660344e27e5107a09c755bfb6cf7a6e48afc92bd
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