Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:1136292
loss:CachedMultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use YesaOuO/ModernBERT-base-CTSP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use YesaOuO/ModernBERT-base-CTSP with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("YesaOuO/ModernBERT-base-CTSP") sentences = [ "During the 1960s Willard Cochrane was U.S. Department of Agriculture's head agricultural economist under U.S. Secretary of Agriculture Orville Freeman.", "Cosmic Smash publisher Sega, platform Dreamcast.", "Willard Cochrane occupation Economist.", "Willard Cochrane educated at Harvard University, educated at Montana State University, date of birth 15 May 1914." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Ctrl+K