Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dataset_size:100K<n<1M
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use Stern5497/nir-2024-xlm-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Stern5497/nir-2024-xlm-roberta-base with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Stern5497/nir-2024-xlm-roberta-base") sentences = [ "who did ezra play for in the nfl", "how many all nba first teams does kobe have", "who does the voice of the little mermaid", "dont come around here no more video director" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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