Feature Extraction
sentence-transformers
Safetensors
English
multi-vector
colbert
late-interaction
Generated from Trainer
dataset_size:50000
loss:MultiVectorMultipleNegativesRankingLoss
Eval Results (legacy)
Instructions to use tomaarsen/multivector-ModernBERT-base-msmarco-peft-no-query-expansion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use tomaarsen/multivector-ModernBERT-base-msmarco-peft-no-query-expansion with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("tomaarsen/multivector-ModernBERT-base-msmarco-peft-no-query-expansion") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Ctrl+K