AI Models
OlaverseMist Reranker 150m
MIST Rerank family · open weights on Hugging Face.
Cross-encoder reranker (150M-parameter ModernBERT) that re-orders retrieved passages by true relevance for search and RAG.
Sentence Transformers
Safetensors
Modernbert
Reranker
Cross Encoder
Retrieval
RAG
Mist
Text Ranking
English
Dataset:olaverse/reranker General En Llm Judged
Base: answerdotai/ModernBERT-base
Base: answerdotai/ModernBERT-base
Licence: apache-2.0
Model Index
Text Embeddings Inference
Endpoints Compatible
0
Likes
77
Downloads
Jun 2026
Created
Model Card
Built for production use.
Quick Start
Use Mist Reranker 150m, straight from its model card.
example.py
from the model cardfrom sentence_transformers import CrossEncoder
model = CrossEncoder("olaverse/mist-reranker-150m")
query = "What causes ocean tides?"
passages = [
"Tides are caused by the gravitational pull of the Moon and Sun on Earth's oceans.",
"The Pacific Ocean is the largest of Earth's oceanic divisions.",
"Tidal energy is a renewable power source generated from the movement of tides.",
]
scores = model.predict([(query, p) for p in passages])
for s, p in sorted(zip(scores, passages), reverse=True):
print(f"{s:.3f} {p}")
Model Card
Official Repository README
Dynamically loaded from Hugging Face
Model card metadata is available on Hugging Face.
Built with
Transformers PyTorch Python
Built by Olaverse Labs
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Cross-encoder reranker (150M-parameter ModernBERT) that re-orders retrieved passages by true relevance for search and RAG.
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