Sentence Similarity
sentence-transformers
ONNX
Safetensors
Russian
modernbert
feature-extraction
text-embeddings-inference
Instructions to use deepvk/USER2-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use deepvk/USER2-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("deepvk/USER2-base") sentences = [ "Это счастливый человек", "Это счастливая собака", "Это очень счастливый человек", "Сегодня солнечный день" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 73b92a063d4c2f275039c49a32c894be1a623d3e00ebd4f5124c7aef23fc178a
- Size of remote file:
- 597 MB
- SHA256:
- 1e186b3ee1d170cb568aae7c1b497e7b7e6d6a65f8442cab8e646034cba35100
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