Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:2234
loss:CoSENTLoss
dataset_size:5749
Eval Results (legacy)
text-embeddings-inference
Instructions to use Shailu1492/mbert-large-mnrl-snli-max2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Shailu1492/mbert-large-mnrl-snli-max2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Shailu1492/mbert-large-mnrl-snli-max2") sentences = [ "Schofield got Toepfer to admit on cross-examination that she ignored many of O'Donnell's suggestions and projects.", "But under cross-examination by O'Donnell's attorney, Lorna Schofield, Toepfer conceded she had ignored many of O'Donnell's suggestions and projects.", "The attack seemed similar to attacks staged near foreign compounds in Riyadh on May 12, for which officials have also blamed al-Qaida.", "In seeking leniency, Waksal apologized to the court, his employees and his family." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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