Feature Extraction
sentence-transformers
Safetensors
English
neobert
sparse-encoder
sparse
splade
Generated from Trainer
dataset_size:630000
loss:SpladeLoss
loss:SparseMultipleNegativesRankingLoss
loss:FlopsLoss
custom_code
Eval Results (legacy)
Instructions to use drexalt/splade-NeoBERT-msmarco-triplets-muon with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use drexalt/splade-NeoBERT-msmarco-triplets-muon with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("drexalt/splade-NeoBERT-msmarco-triplets-muon", trust_remote_code=True) 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