Sentence Similarity
sentence-transformers
Safetensors
Russian
modernbert
feature-extraction
code-retrieval
1c
bsl
matryoshka
Eval Results (legacy)
text-embeddings-inference
Instructions to use PruhaNLP/USER2-1C-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use PruhaNLP/USER2-1C-code with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("PruhaNLP/USER2-1C-code") 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
апдейт ридми
Browse files
README.md
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## Код валидации
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Eval
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[`github.com/PruhaNLP/1C-
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## Правовая информация
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## Код валидации
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Eval метод опубликован отдельно:
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[`https://github.com/PruhaNLP/1C-RB`](https://github.com/PruhaNLP/1C-RB).
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