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Rubert Base Cased Sentence
R
Rubert Base Cased Sentence
Developed by DeepPavlov
Representation-based Russian sentence encoder that obtains sentence representations by averaging token embedding vectors
Downloads 14.18k
Release Time : 3/2/2022
Model Overview
This model is a Russian sentence encoder initialized based on RuBERT, specifically designed to generate high-quality sentence-level embeddings. It has been fine-tuned on the translated SNLI dataset and the Russian portion of the XNLI development set, making it suitable for Russian natural language processing tasks.
Model Features
Russian optimization
Specially optimized and fine-tuned for Russian, providing high-quality Russian sentence representations
RuBERT-based
Initialized with the powerful RuBERT model, inheriting its excellent language understanding capabilities
Sentence-level representation
Uses mean pooling to generate sentence-level embeddings, suitable for downstream tasks like sentence similarity
Multi-dataset fine-tuning
Fine-tuned specifically on SNLI and XNLI datasets, enhancing the model's generalization ability
Model Capabilities
Sentence embedding generation
Sentence similarity calculation
Text semantic analysis
Russian natural language processing
Use Cases
Semantic similarity
Russian sentence similarity calculation
Calculate the semantic similarity between two Russian sentences
Can be used in applications like information retrieval and question-answering systems
Information retrieval
Russian document retrieval
Russian document retrieval system based on semantic similarity
Improves the relevance of retrieval results
Text classification
Russian sentiment analysis
Russian text sentiment classification based on sentence embeddings
Accurately identifies the emotional tendency of Russian texts
Transformers
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