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Sponsored by
AdsCreator.com
AXERA-TECH / siglip2-base-patch16-224
Model's Last Updated: February 04 2026
zero-shot-classification
Introduction of siglip2-base-patch16-224
Model Details of siglip2-base-patch16-224
SigLIP2
SigLIP 2 extends the pretraining objective of SigLIP with prior, independently developed techniques into a unified recipe, for improved semantic understanding, localization, and dense features. You can use the raw model for tasks like zero-shot image classification and image-text retrieval, or as a vision encoder for VLMs (and other vision tasks).
The Original repo is https://huggingface.co/google/siglip2-base-patch16-224 .
This model of SigLIP has been converted to run on the Axera NPU using w8a16 quantization.
This model has been optimized with the following LoRA:
Compatible with Pulsar2 version: 5.1
Convert tools links:
For those who are interested in model conversion, you can try to export axmodel through
-
The repo of AXera Platform , which you can get the detial of guide
Support Platform
| Models | latency |
|---|---|
| Image Encoder | 11.1ms |
| Text Encoder | 4.56ms |
How to use
Download all files from this repository to the device
root@ax650:~/siglip2-base-patch16-224# tree -L 2
.
├── 000000039769.jpg
├── README.md
├── ax650
│ ├── siglip2-base-patch16-224_text.axmodel
│ └── siglip2-base-patch16-224_vision.axmodel
├── config.json
├── model_convert
│ ├── imagenet-calib.tar
│ ├── siglip2-base-patch16-224_text.json
│ └── siglip2-base-patch16-224_vision.json
├── onnx
│ ├── siglip2-base-patch16-224_text.onnx
│ └── siglip2-base-patch16-224_vision.onnx
├── python
│ ├── axmodel_infer.py
│ ├── export_onnx.py
│ ├── onnx_infer.py
│ ├── requirements.txt
│ └── test.py
└── tokenizer
├── config.json
├── preprocessor_config.json
├── special_tokens_map.json
├── tokenizer.json
└── tokenizer_config.json
5 directories, 20 files
python env requirement
pyaxengine
https://github.com/AXERA-TECH/pyaxengine
wget https://github.com/AXERA-TECH/pyaxengine/releases/download/0.1.3rc0/axengine-0.1.3-py3-none-any.whl
pip install axengine-0.1.3-py3-none-any.whl
others
pip install -r python/requirements.txt
Inputs
Test
"a photo of 2 cats", "a photo of 2 dogs"
Image
Inference with AX650 Host, such as M4N-Dock(爱芯派Pro)
root@ax650:~/siglip2-base-patch16-224# python3 python/axmodel_infer.py
[INFO] Available providers: ['AxEngineExecutionProvider']
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Chip type: ChipType.MC50
[INFO] VNPU type: VNPUType.DISABLED
[INFO] Engine version: 2.12.0s
[INFO] Model type: 2 (triple core)
[INFO] Compiler version: 5.1-patch1 430ee3be
[INFO] Using provider: AxEngineExecutionProvider
[INFO] Model type: 2 (triple core)
[INFO] Compiler version: 5.1-patch1 430ee3be
[[1.0596762e-01 1.9978019e-05]]
10.6% that image 0 is 'a photo of 2 cats'
Runs of AXERA-TECH siglip2-base-patch16-224 on huggingface.co
34
Total runs
3
24-hour runs
6
3-day runs
7
7-day runs
14
30-day runs
More Information About siglip2-base-patch16-224 huggingface.co Model
Url of siglip2-base-patch16-224
siglip2-base-patch16-224 huggingface.co Url
Provider of siglip2-base-patch16-224 huggingface.co
Other API from AXERA-TECH
Updated:August 26 2026
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