Sentence Similarity
sentence-transformers
Safetensors
French
English
xlm-roberta
evalllm2026
text-embeddings-inference
Instructions to use rarmingaud/evalllm2026-mesh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use rarmingaud/evalllm2026-mesh with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rarmingaud/evalllm2026-mesh") sentences = [ "C'est une personne heureuse", "C'est un chien heureux", "C'est une personne très heureuse", "Aujourd'hui est une journée ensoleillée" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- abc0255193ec5adea50155386b9d955a5fef2a97e717725806d23a145e2c240b
- Size of remote file:
- 17.1 MB
- SHA256:
- c9aa11237e0fea37d30303dbde2d3a79e6139e531f8aaaad7ed1f04383178d6f
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