Memoria Mobile Vision Assets

--- license: apple-amlr library_name: onnx tags: - mobileclip - mobileclip2 - mobileviclip - onnx - tflite - ncnn - quantization - edge-ai - mobile-ai - vision-language-model - memoria pipeline_tag: zero-shot-image-classification --- # Memoria Mobile Vision Assets Deployment-ready mobile vision-language encoder assets for the Memoria project, including ONNX/TFLite/NCNN exports, validation scripts, and release tooling. This release focuses on Memoria's mobile deployment scenario. It does not claim to be the first public ONNX/TFLite export of MobileCLIP or MobileCLIP2. ## Released Models | Model | ONNX | TFLite | NCNN | Text Encoder | Validation | | --- | --- | --- | --- | --- | --- | | mobileclip-s2 | 137.6 MB | 68.4 MB float16 | 6 files, 378.2 MB | - | ONNX cosine >= 0.99999988; NCNN cosine >= 0.99999988 vs ONNX | | mobileclip2-s0 | 43.4 MB | - | - | 242.3 MB ONNX | ONNX cosine >= 0.99999988 | | mobileclip2-s2 | 136.4 MB | - | - | 242.3 MB ONNX | ONNX cosine >= 0.99999994 | | mobileclip2-b | 329.5 MB | - | - | 242.5 MB ONNX | ONNX cosine >= 0.99999988 | | mobileviclip-small-frame-encoder | 67.3 MB | - | raw + optimized NCNN, 67.5 MB | - | ONNX-vs-NCNN cosine >= 0.9997077584 | ## Validation | Model | Backend | Min Cosine | Max Abs Error | Status | | --- | --- | --- | --- | --- | | mobileclip-s2 | ONNX | 0.99999988 | 8.05e-07 | passed | | mobileclip-s2 | TFLite fp16 | 0.99997151 | 1.38e-03 | passed | | mobileclip-s2 | NCNN image encoder | 0.99999988 | 1.47e-04 | passed | | mobileclip2-s0 | ONNX | 0.99999988 | 2.98e-07 | passed | | mobileclip2-s2 | ONNX | 0.99999994 | 5.36e-07 | passed | | mobileclip2-b | ONNX | 0.99999988 | 2.15e-06 | passed | | mobileviclip-small-frame-encoder | ONNX-vs-NCNN frame feature-map | 0.9997077584 | 1.745875776e-01 | passed | ONNX and available TFLite artifacts were numerically validated against the PyTorch reference model. NCNN artifacts were validated against their ONNX exports. ## Reproducibility Each model directory contains: - `model.onnx` - `model.int8.tflite`, when supported and present - `model.ncnn.param` / `model.ncnn.bin`, when supported and present - `config.json` - `metrics.json` - `README.md` - `scripts/` with export, validation, quantization, and upload helpers Build v0.1 locally from the Memoria repository: ```bash python ai_tools/mobile_vision_release/export_mobile_vision_...

Source context: 20 downloads · 0 likes · Pipeline zero-shot-image-classification · Library onnx · Repo youthfedpycharm/memoria-mobile-vision-assets