Sentence Similarity
sentence-transformers
Safetensors
Russian
bert
feature-extraction
semantic-search
russian
domain-adaptation
text-embeddings-inference
Instructions to use AtesiT/all-MiniLM-L6-v2-ru-adapted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use AtesiT/all-MiniLM-L6-v2-ru-adapted with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("AtesiT/all-MiniLM-L6-v2-ru-adapted") 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
Download 1_Pooling/config.json from AtesiT/all-MiniLM-L6-v2-ru-adapted: direct link, hf CLI and curl.
- Browser
- Download file 90 Bytes
-
https://huggingface.co/AtesiT/all-MiniLM-L6-v2-ru-adapted/resolve/main/1_Pooling/config.json
- Command line
-
hf download hf://AtesiT/all-MiniLM-L6-v2-ru-adapted/1_Pooling/config.json
-
curl -L -o config.json https://huggingface.co/AtesiT/all-MiniLM-L6-v2-ru-adapted/resolve/main/1_Pooling/config.json
90 Bytes
| { | |
| "embedding_dimension": 384, | |
| "pooling_mode": "mean", | |
| "include_prompt": true | |
| } |