Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
Generated from Trainer
dataset_size:557850
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use sartifyllc/swahili-paraphrase-multilingual-mpnet-base-v2-nli-matryoshka with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sartifyllc/swahili-paraphrase-multilingual-mpnet-base-v2-nli-matryoshka with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sartifyllc/swahili-paraphrase-multilingual-mpnet-base-v2-nli-matryoshka") sentences = [ "Mwanamume aliyepangwa vizuri anasimama kwa mguu mmoja karibu na pwani safi ya bahari.", "mtu anacheka wakati wa kufua nguo", "Mwanamume fulani yuko nje karibu na ufuo wa bahari.", "Mwanamume fulani ameketi kwenye sofa yake." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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