Sentence Similarity
sentence-transformers
Safetensors
Russian
English
bert
embeddings
vllm
inference-optimized
inference
text-embeddings-inference
Instructions to use WpythonW/rubert-tiny2-vllm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use WpythonW/rubert-tiny2-vllm with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("WpythonW/rubert-tiny2-vllm") 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] - Notebooks
- Google Colab
- Kaggle
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README.md
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language:
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- ru
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pipeline_tag: sentence-similarity
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tags:
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- english
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- russian
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- embeddings
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- sentence-transformers
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- vllm
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- inference-optimized
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license: mit
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base_model: cointegrated/rubert-tiny2
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language:
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- en
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pipeline_tag: sentence-similarity
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tags:
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- embeddings
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- sentence-transformers
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- vllm
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- inference
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license: mit
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base_model: cointegrated/rubert-tiny2
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