Sentence Similarity
sentence-transformers
PyTorch
Transformers
Russian
bert
feature-extraction
text-embeddings-inference
Instructions to use inkoziev/sbert_pq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use inkoziev/sbert_pq with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("inkoziev/sbert_pq") sentences = [ "Кошка ловит мышку.", "Кто ловит мышку?", "Где живет кошка?", "Как мышку зовут?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use inkoziev/sbert_pq with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("inkoziev/sbert_pq") model = AutoModel.from_pretrained("inkoziev/sbert_pq") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
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