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chore: add support for quantized versions of CV models CLIP, Style Transfer, EfficientNetV2, SSDLite#940

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@bh/quantize-cv-models
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chore: add support for quantized versions of CV models CLIP, Style Transfer, EfficientNetV2, SSDLite#940
barhanc wants to merge 6 commits intomainfrom
@bh/quantize-cv-models

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@barhanc
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@barhanc barhanc commented Mar 6, 2026

Description

Adds support for quantized versions of CV models CLIP, Style Transfer, EfficientNetV2, SSDLite and updates paths to non-quantized models exported with ExecuTorch v1.1.0.

Introduces a breaking change?

  • Yes
  • No

Type of change

  • Bug fix (change which fixes an issue)
  • New feature (change which adds functionality)
  • Documentation update (improves or adds clarity to existing documentation)
  • Other (chores, tests, code style improvements etc.)

Tested on

  • iOS
  • Android

Testing instructions

  1. Run the Computer Vision example app:
    • Object detection with model set to:
      • SSDLITE_320_MOBILENET_V3_LARGE
    • Classification with model set to:
      • EFFICIENTNET_V2_S,
      • EFFICIENTNET_V2_S_QUANTIZED
    • Style transfer with model set to:
      • STYLE_TRANSFER_CANDY,
      • STYLE_TRANSFER_MOSAIC,
      • STYLE_TRANSFER_UDNIE,
      • STYLE_TRANSFER_RAIN_PRINCESS,
      • STYLE_TRANSFER_CANDY_QUANTIZED,
      • STYLE_TRANSFER_MOSAIC_QUANTIZED,
      • STYLE_TRANSFER_UDNIE_QUANTIZED,
      • STYLE_TRANSFER_RAIN_PRINCESS_QUANTIZED,
  2. Run the Text Embeddings example app:
    • CLIP embeddings with image model set to:
      • CLIP_VIT_BASE_PATCH32_IMAGE,
      • CLIP_VIT_BASE_PATCH32_IMAGE_QUANTIZED
  3. Check HF pages for updated models:

Screenshots

Related issues

Closes #719

Checklist

  • I have performed a self-review of my code
  • I have commented my code, particularly in hard-to-understand areas
  • I have updated the documentation accordingly
  • My changes generate no new warnings

Additional notes

@barhanc barhanc self-assigned this Mar 6, 2026
@barhanc barhanc added chore PRs that are chores model Issues related to exporting, improving, fixing ML models labels Mar 6, 2026
@NorbertKlockiewicz
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I will run the new models later today to see if they work. I think you should also benchmark them and add the results to our docs.

You can ask @IgorSwat for the tips about benchmarking ;D

@IgorSwat
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IgorSwat commented Mar 6, 2026

@barhanc Did you profile the added XNNPACK models following these instructions?

I guess they should be fine considering that those are only a quantized versions of already profiled models, but it's always nice to check if everything is alright with export.

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Quantize CV models

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