Organization

Påmin Labs

pamin-labs

Retrieval、Embeddings、Reranking、Agent memory、ONNX、Quantization

Models in Library1

Datasets in Library0

Models on Hugging Face1

Followers2

Compare the published evidence

This profile connects the 1 model and dataset record shown below to their upstream cards and sources. The library counts describe SAVRN's coverage, rather than this publisher's entire output.

Published tasks: Feature extraction.

Reported licenses: apache-2.0. Open a record to review its specific license and conditions.

Compare model specifications, source dates, and hardware estimates on the individual records. Publisher identity verification is separate from a model's quality, deployment readiness, or suitability for your work.

Models

Model · Feature extraction

embeddinggemma-2-text-int8-onnx

Påmin Labs

The text encoder of google/embeddinggemma-2 (Google DeepMind, Apache-2.0), exported to ONNX and quantized to int8 for ONNX Runtime on CPU. It returns the same kind of vector as the original model: a 768-dimensional, L2-normalised text embedding. Its output for a text does not depend on what else is in the batch: the vectors are bitwise identical at every batch size we tested. This is a modified version of the original model, not a retrained one. It is the dense retrieval model of Påmin Memory, and it can be used on its own with any ONNX Runtime application. Sizes are file sizes in bytes / 10^6. The text tower sizes come from the upstream checkpoint's safetensors header: the languagemodel.…

Open weights apache-2.0 262,144 tokens onnx

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