Spaces:
Running
title: DUSUNEN Search Lab
emoji: 🔎
colorFrom: indigo
colorTo: blue
sdk: static
app_file: index.html
pinned: false
license: mit
short_description: Private, in-browser Turkish semantic search with ONNX
models:
- GoktugD/DUSUNEN-Rota-270M-v1
datasets:
- GoktugD/DUSUNEN-Retrieval-100K-v1
tags:
- sentence-transformers
- semantic-search
- turkish
- information-retrieval
DUSUNEN Search Lab
An interactive, zero-server demonstration of
GoktugD/DUSUNEN-Rota-270M-v1.
The validated mixed-precision model runs locally in the visitor's browser through ONNX Runtime and WebAssembly. Its embedding table uses int8 while the transformer blocks remain float; measured mean PyTorch-to-ONNX embedding cosine agreement is 0.999956. Search text is not sent to an inference API. The app ranks an original Turkish technology-and-science corpus with cosine similarity. This demo corpus is separate from both the MS MARCO-derived training set and the TurHistQuad benchmark.
Measured benchmark results and the complete training recipe are linked from the model card. Similarity scores are ranking signals, not calibrated probabilities.
Built with the free Static Spaces runtime; no paid inference endpoint is used.