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lenta-w2v-cbow-300d

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[Lenta Word2Vec CBOW 300D]

🗃️ Corpus

109k+ words from lenta.ru (2025)

⚙️ Параметры

Algorithm: Word2Vec CBOW
Vector size: 300
Window size: 10
Min frequency: 10

📊 Metrics

Word analogy accuracy: 42.86%
Semantic similarity correlation: 0.18
Vocabulary coverage: 28.76%

💻 Use case

from gensim.models import Word2Vec
model = Word2Vec.load("lenta_w2v_cbow_300d.model")
similar = model.wv.most_similar("путин")

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