Instructions to use mobilint/RepViT_M3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Mobilint
How to use mobilint/RepViT_M3 with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="RepViT_M3", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
Publish approved Variant MXQ
Browse files- README.md +62 -10
- aries-rb/metadata.json +51 -0
- aries-rb/repvit_m3.mxq +2 -2
- aries/best_result.json +0 -1
- aries/repvit_m3.mxq +0 -3
README.md
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- timm/repvit_m3.dist_in1k
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---
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<a href="https://mobilint.com">
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<img src="https://raw.githubusercontent.com/mobilint/.github/main/assets/Mobilint_Logo_Primary.png?raw=true"
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width="50%"
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alt="mobilint" />
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</a>
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</div>
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- timm/repvit_m3.dist_in1k
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---
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# RepViT_M3
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`aries-rb/` holds the MXQ reproduced from the published arxiv folder (https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/RepViT_M3). It was compiled by qbcompiler 1.4.0 in the image `mobilint/qbcompiler:1.4-cuda12.8.1-ubuntu22.04` (sha256:7910f1661605b82eb9616f6ac99fd6461dbb865dcadaa810cce22c638ceffd44) with `--inference-scheme single`, so it supports the core mode(s) `single` only.
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It was evaluated with qbruntime 1.5.0 in `async` inference mode on imagenet (50000 samples): top1_accuracy 0.81262, top5_accuracy 0.95492. Only the evaluated core mode was measured.
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SHA-256: `f260cd738b709d41e378affbe3dad8c26b9ea09e16a80cfd7df18fb78ab7ac31` (10976273 bytes). Verify a download with `sha256sum <file>.mxq` and compare the digest with this value and with `aries-rb/metadata.json`.
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aries-rb/best_result.json contains legacy build values and is retained for mblt-vision-python compile defaults.
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The legacy aries/ directory was removed; mblt-model-zoo <= 2.12 must pin an older revision.
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```json
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{
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"schema_version": 2,
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"model": "RepViT_M3",
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"variant": "c0923-gptaq",
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"qbcompiler": "1.4.0",
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"qbruntime": "1.5.0",
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"compile": {
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"image_tag": "1.4-cuda12.8.1-ubuntu22.04",
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"image_digest": "sha256:7910f1661605b82eb9616f6ac99fd6461dbb865dcadaa810cce22c638ceffd44",
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"inference_scheme": "single",
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"device": "gpu"
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},
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"evaluation": {
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"dataset": "imagenet",
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"sample_count": 50000,
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"primary": {
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"top1_accuracy": 0.81262
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},
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"secondary": {
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"top5_accuracy": 0.95492
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},
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"protocol": null,
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"eval_data_identity": null,
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"identity_audit": "absent",
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"inference_mode": "async",
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"image_tag": "1.4-cpu-ubuntu22.04",
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"image_digest": "sha256:62b5bc714571dffd94fb561275767ca80d15337a433630a3ae7936305d531a7b"
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},
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"retention_percent": {
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"top1_accuracy": 99.72265855095227
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},
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"content_sha256": "02bcebd7ca8c74852a921747955cb3d11748c8402f6a1a423b9c7ec27ee1657f",
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"attempt_id": "srcmodes8-repvit-m3-20261009t164855-r1",
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"superseded_attempt_ids": [
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"srcmodes8-repvit-m3-20261009t164855"
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],
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"sha256": "f260cd738b709d41e378affbe3dad8c26b9ea09e16a80cfd7df18fb78ab7ac31",
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"format": "MXQv7",
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"supported_modes": [
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"single"
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],
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"size": 10976273,
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"ops_commits": {
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"selection": "2505304b714b87f620665f0d55ac9ce99d6c57e6"
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},
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"arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/RepViT_M3",
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"publication": {
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"status": "public",
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"reason": "approved"
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}
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}
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```
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aries-rb/metadata.json
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{
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"schema_version": 2,
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"model": "RepViT_M3",
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"variant": "c0923-gptaq",
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"qbcompiler": "1.4.0",
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"qbruntime": "1.5.0",
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"compile": {
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"image_tag": "1.4-cuda12.8.1-ubuntu22.04",
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"image_digest": "sha256:7910f1661605b82eb9616f6ac99fd6461dbb865dcadaa810cce22c638ceffd44",
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"inference_scheme": "single",
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"device": "gpu"
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},
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"evaluation": {
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"dataset": "imagenet",
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"sample_count": 50000,
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"primary": {
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"top1_accuracy": 0.81262
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},
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"secondary": {
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"top5_accuracy": 0.95492
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},
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"protocol": null,
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"eval_data_identity": null,
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"identity_audit": "absent",
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"inference_mode": "async",
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"image_tag": "1.4-cpu-ubuntu22.04",
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"image_digest": "sha256:62b5bc714571dffd94fb561275767ca80d15337a433630a3ae7936305d531a7b"
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},
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"retention_percent": {
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"top1_accuracy": 99.72265855095227
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},
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"content_sha256": "02bcebd7ca8c74852a921747955cb3d11748c8402f6a1a423b9c7ec27ee1657f",
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"attempt_id": "srcmodes8-repvit-m3-20261009t164855-r1",
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"superseded_attempt_ids": [
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"srcmodes8-repvit-m3-20261009t164855"
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],
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"sha256": "f260cd738b709d41e378affbe3dad8c26b9ea09e16a80cfd7df18fb78ab7ac31",
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"format": "MXQv7",
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"supported_modes": [
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"single"
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],
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"size": 10976273,
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"ops_commits": {
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"selection": "2505304b714b87f620665f0d55ac9ce99d6c57e6"
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+
},
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"arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/RepViT_M3",
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"publication": {
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"status": "public",
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"reason": "approved"
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}
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}
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aries-rb/repvit_m3.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:f260cd738b709d41e378affbe3dad8c26b9ea09e16a80cfd7df18fb78ab7ac31
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size 10976273
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aries/best_result.json
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{"acc": 0.80896, "timestamp": 1779433931, "checkpoint_dir_name": null, "done": true, "training_iteration": 1, "trial_id": "85a0b1b7", "date": "2026-05-22_16-12-11", "time_this_iter_s": 500.75350284576416, "time_total_s": 500.75350284576416, "pid": 3437235, "hostname": "ae30e054f296", "node_ip": "172.17.0.3", "config": {"percentile": 0.0010809651577368944, "topk": 0.037116180077902065}, "time_since_restore": 500.75350284576416, "iterations_since_restore": 1, "experiment_tag": "9_percentile=0.0011,topk=0.0371"}
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aries/repvit_m3.mxq
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version https://git-lfs.github.com/spec/v1
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oid sha256:8778ea55ef14b5b07ad190133bb43a917085480aab3c9acdc92971533739ee5e
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size 12125405
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