---
license: apache-2.0
base_model:
- google/siglip-so400m-patch14-384
pipeline_tag: zero-shot-image-classification
tags:
- renesas
- x5h
- coming-soon
- cv
- vision
---

# SigLIP-SO400M – Renesas X5H

<p align="center">
  <img src="https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/model_doc/siglip_table.jpeg" alt="SigLIP vs. CLIP zero-shot and retrieval benchmark comparison" width="640">
</p>
<p align="center"><sub>SigLIP vs. CLIP evaluation results, from the original paper — as shown on the official <a href="https://huggingface.co/google/siglip-so400m-patch14-384">google/siglip-so400m-patch14-384</a> model card</sub></p>

🚧 **Coming soon.** This model is being optimized and validated for Renesas hardware — no fixed release date yet.

## Introduction

**SigLIP-SO400M** is Google's Sigmoid-Loss vision-language embedding model (the "shape-optimized" 400M-parameter variant), commonly used as a vision encoder for zero-shot image classification and retrieval. Renesas is preparing an optimized deployment of this model for the R-Car Gen5 platform.

- **Model Architecture:** SigLIP vision/text dual encoder (vision tower only is the focus for on-device deployment).
- **Source Model:** [google/siglip-so400m-patch14-384](https://huggingface.co/google/siglip-so400m-patch14-384)

*This page is a placeholder. Content is provisional and subject to change before the model is fully published.*