Sentence Similarity
sentence-transformers
Safetensors
Transformers
bert
feature-extraction
text-embeddings-inference
Instructions to use basic-go/math-ru-sbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use basic-go/math-ru-sbert with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("basic-go/math-ru-sbert") 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 basic-go/math-ru-sbert with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("basic-go/math-ru-sbert") model = AutoModel.from_pretrained("basic-go/math-ru-sbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 1,356 Bytes
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library_name: sentence-transformers
pipeline_tag: sentence-similarity
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
# basic-go/math-ru-sbert
Это [Sentence Transformer](https://www.SBERT.net), предназначенный для векторизации текстов с математическими выражениями. Полученные векторные представления могут использоваться для выявления дубликатов, оценки семантического сходства и информационного поиска.
## Использование
Вместе с предустановленной библиотекой [sentence-transformers](https://www.SBERT.net) модель можно использовать следующим образом:
```python
from sentence_transformers import SentenceTransformer
sentences = [r"\(\int \rho(x) dx\)"]
model = SentenceTransformer('basic-go/math-ru-sbert')
embeddings = model.encode(sentences)
print(embeddings)
```
Вместе с тем рекомендуется использовать модель в составе библиотеки [Emma](https://github.com/basic-go-ahead/emma) для актуальной пред- и постобработки данных.
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