Sentence Similarity
sentence-transformers
Safetensors
neobert
feature-extraction
Generated from Trainer
dataset_size:130899
loss:MultipleNegativesRankingLoss
custom_code
Instructions to use ashercn97/neobert-multi-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ashercn97/neobert-multi-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ashercn97/neobert-multi-nli", trust_remote_code=True) sentences = [ "Also, Lou Reed is tough.", "Lou Reed is tough.", "The snow was so deep in the field that if you fell, you wouldn't feel it.", "Some organizations don't like change." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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