Six Navers Lab / Einsia benchmarks and the work they test
Compare the tasks, scoring and evidence behind six Einsia benchmarks, with complete Radar detail pages and original references.
Claire Radar
An end-to-end ONNX quantization benchmark for a DistilBERT sentiment classifier, comparing PyTorch FP32, ONNX FP32, dynamic INT8, and static INT8 variants on accuracy, latency, and model size using a fixed 200-sample SST-2 validation set.
Numeric results have not been collected for this source record. Use the paper, code or dataset below to check the task and experiments; this does not imply that the original work contains no results.
Catalog collected on 2026-10-14; resources and fields reflect that saved source.
Observed on: 2026-10-14
parth-udawant/distilbert-onnx-quantization-benchmark · View source snapshot
Dated attention observations, not live counts or benchmark scores.
These are source-reported observations, not independent reruns by this site. Check the task version, evaluation protocol, unit and reporting date before comparing models. Results from different setups are not a universal ranking.
This source record has no numeric results in our collection. That does not mean a score of zero or that no public results exist. Consult the original resources above.