Sentence Similarity
sentence-transformers
Safetensors
Transformers
Russian
English
bert
feature-extraction
russian
pretraining
embeddings
tiny
mteb
text-embeddings-inference
Instructions to use sergeyzh/rubert-tiny-topic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sergeyzh/rubert-tiny-topic with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sergeyzh/rubert-tiny-topic") 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] - Transformers
How to use sergeyzh/rubert-tiny-topic with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("sergeyzh/rubert-tiny-topic") model = AutoModel.from_pretrained("sergeyzh/rubert-tiny-topic") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d35c477174a7c63520a19f79610520849df3f2d7c0001b7fa998d2cce070f98
- Size of remote file:
- 92.2 MB
- SHA256:
- 37238144305ea448a38c334fd781f8ed0736aa33f13d4e044b15479c30441d02
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