| --- |
| license: apache-2.0 |
| base_model: Marqo/marqo-fashionCLIP |
| library_name: litert |
| tags: |
| - litert |
| - tflite |
| - fashion |
| - image-feature-extraction |
| --- |
| |
| # Marqo-FashionCLIP image encoder, LiteRT dynamic int8 |
|
|
| The image tower of [Marqo/marqo-fashionCLIP](https://huggingface.co/Marqo/marqo-fashionCLIP) |
| (revision `44f4c655124ed71e90cbf528d82f508d69d8a81b`), converted to LiteRT and quantised. The |
| Robbeta Android app downloads it to compare outfit photos with the clothes in a wardrobe, on |
| the phone. |
|
|
| | File | Bytes | SHA-256 | |
| |---|---|---| |
| | `marqo-fashionclip-image-dynint8-v1.tflite` | 88 160 672 | `8aa00548e4f7768f97c9c11f1130d646bd6c1cf6b980451b5e9609a8295427b6` | |
|
|
| A later model gets a new file name; this file never changes. |
|
|
| ## Input and output |
|
|
| - Input `[1, 3, 224, 224]` float32, NCHW, RGB. |
| - Output `[1, 512]` float32, not normalised. Normalise it (L2) before taking cosines. |
| - Preprocessing, as open_clip does for this model: resize the shorter side to 224 with Pillow |
| bicubic, then centre-crop to 224 x 224 (Robbeta pads to a square first, so nothing is |
| cropped), scale to 0..1, subtract mean `(0.48145466, 0.4578275, 0.40821073)` and divide by std |
| `(0.26862954, 0.26130258, 0.27577711)`. |
| |
| ## How it was made |
| |
| `litert-torch` 0.9.4 converted `model.visual` from open_clip 3.3.0 (torch 2.13.0) to a float32 |
| `.tflite`; `ai-edge-quantizer` 0.9.0 then applied the `dynamic_wi8_afp32` recipe (int8 weights, |
| float activations, dynamic-range int8 matmuls). The script is `tools/matcher/convert.py` in the |
| Robbeta repository. |
|
|
| ## Licence |
|
|
| Apache-2.0, the licence of the original model (see `LICENSE`). This file is a modified version |
| of Marqo-FashionCLIP's weights: converted to LiteRT and quantised to int8. Marqo-FashionCLIP is |
| by Marqo; see the original model card for its training data and evaluation. |
|
|
