Sentence Similarity
sentence-transformers
Safetensors
Russian
bert
feature-extraction
triplet-loss
domain-adaptation
text-embeddings-inference
Instructions to use F1ow421/all-MiniLM-L6-v2-ru-hnp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use F1ow421/all-MiniLM-L6-v2-ru-hnp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("F1ow421/all-MiniLM-L6-v2-ru-hnp") 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 output.png from F1ow421/all-MiniLM-L6-v2-ru-hnp: direct link, hf CLI and curl.
- Browser
- Download file 321 kB
-
https://huggingface.co/F1ow421/all-MiniLM-L6-v2-ru-hnp/resolve/main/output.png
- Command line
-
hf download hf://F1ow421/all-MiniLM-L6-v2-ru-hnp/output.png
-
curl -L -o output.png https://huggingface.co/F1ow421/all-MiniLM-L6-v2-ru-hnp/resolve/main/output.png
321 kB

- Xet hash:
- eea03e52a119712f6e5eecf1c57d5c037bcf962b527bb7453b6d5d7fa1902a20
- Size of remote file:
- 321 kB
- SHA256:
- 6914bdb791935cfc86becb40aad7aa60ace872a692740ee5a3c2065d0b1e047b
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