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 model.safetensors from AtesiT/all-MiniLM-L6-v2-ru-adapted: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/AtesiT/all-MiniLM-L6-v2-ru-adapted/resolve/main/model.safetensors
- Command line
-
hf download hf://AtesiT/all-MiniLM-L6-v2-ru-adapted/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/AtesiT/all-MiniLM-L6-v2-ru-adapted/resolve/main/model.safetensors
90.9 MB
- Xet hash:
- 84e42e24552e3be0ef1a1710227f6e39980d52e2502bb0cb7b42831c4c7e39fc
- Size of remote file:
- 90.9 MB
- SHA256:
- 9346cdd469586f069041c0011adec3ebcb8b22501647c2ae8f403435f91b5426
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