Sentence Similarity
Model2Vec
Safetensors
sentence-transformers
Ukrainian
static-embeddings
embeddings
retrieval
ukrainian
Instructions to use SyntaxSpirits/ukr-static-m3-64k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use SyntaxSpirits/ukr-static-m3-64k with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("SyntaxSpirits/ukr-static-m3-64k") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - sentence-transformers
How to use SyntaxSpirits/ukr-static-m3-64k with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SyntaxSpirits/ukr-static-m3-64k") 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] - Notebooks
- Google Colab
- Kaggle
Commit History
14 days ago
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Add ukr-static-m3-64k: Ukrainian static embedding model, card, license and notice
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