Sentence Similarity
sentence-transformers
Safetensors
distilbert
feature-extraction
Generated from Trainer
dataset_size:1327190
loss:CoSENTLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use RomainDarous/preTrained_meanPooling_mistranslationModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use RomainDarous/preTrained_meanPooling_mistranslationModel with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("RomainDarous/preTrained_meanPooling_mistranslationModel") sentences = [ "यहाँका केही धार्मिक सम्पदाहरू यस प्रकार रहेका छन्।", "A party works journalists from advertisements about a massive Himalayan post.", "Some religious affiliations here remain.", "In Spain, the strict opposition of Roman Catholic churches is found to have assumed a marriage similar to male beach wives." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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