Sentence Similarity
sentence-transformers
PyTorch
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use ys7yoo/kosbert_sts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ys7yoo/kosbert_sts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ys7yoo/kosbert_sts") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use ys7yoo/kosbert_sts with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ys7yoo/kosbert_sts") model = AutoModel.from_pretrained("ys7yoo/kosbert_sts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6fbdb83737e5e3e93bffdd75c83eae61da9edb1266037460798c13aa2ba227f3
- Size of remote file:
- 443 MB
- SHA256:
- b81d4878fcc5f53462ad725b743da691e3694cf3e6551c7796735afd0ed9a072
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