Sentence Similarity
sentence-transformers
Safetensors
English
Russian
xlm-roberta
text-embeddings-inference
Instructions to use seniichev/me5-wb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use seniichev/me5-wb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("seniichev/me5-wb") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4a4aba5260b9683078fe48f8aed1e63fdb58019a5235bd93885acaa5cc8ca470
- Size of remote file:
- 1.11 GB
- SHA256:
- c7b439c4d3a0a37d60bbf1ecb815bf6d306383387f42f7fb49a609052a7c925d
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