EfficientFormer_L3

aries-rb/ holds the MXQ reproduced from the published arxiv folder (https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/EfficientFormer_L3). 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 all, so it supports the core mode(s) single, multi, global4, global8 only.

It was evaluated with qbruntime 1.5.0 in async inference mode on imagenet (50000 samples): top1_accuracy 0.80986, top5_accuracy 0.95296. Only the evaluated core mode was measured.

SHA-256: 7b7c1fb28c6b02da867b0d693dd933b19ea009179e57d346efb598ab899b1f54 (34715564 bytes). Verify a download with sha256sum <file>.mxq and compare the digest with this value and with aries-rb/metadata.json.

aries-rb/best_result.json contains legacy build values and is retained for mblt-vision-python compile defaults. The legacy aries/ directory was removed; mblt-model-zoo <= 2.12 must pin an older revision.

{
  "schema_version": 2,
  "model": "EfficientFormer_L3",
  "variant": "c0923-gptaq",
  "qbcompiler": "1.4.0",
  "qbruntime": "1.5.0",
  "compile": {
    "image_tag": "1.4-cuda12.8.1-ubuntu22.04",
    "image_digest": "sha256:7910f1661605b82eb9616f6ac99fd6461dbb865dcadaa810cce22c638ceffd44",
    "inference_scheme": "all",
    "device": "gpu"
  },
  "evaluation": {
    "dataset": "imagenet",
    "sample_count": 50000,
    "primary": {
      "top1_accuracy": 0.80986
    },
    "secondary": {
      "top5_accuracy": 0.95296
    },
    "protocol": null,
    "eval_data_identity": {
      "annotation_sha256": "f00550c10ff1d4110abc683786b6cc09d5082dadd3cee1568f5cfa1dad962960",
      "sample_list_sha256": "54446819dced83110352e5a0361ff05b19c331c5a9802dcb0222e6d1e44a0547"
    },
    "identity_audit": "verified",
    "inference_mode": "async",
    "image_tag": "1.4-cpu-ubuntu22.04",
    "image_digest": "sha256:62b5bc714571dffd94fb561275767ca80d15337a433630a3ae7936305d531a7b"
  },
  "retention_percent": {
    "top1_accuracy": 98.10063715870824
  },
  "content_sha256": "970bc60046f7a5d657ba9fb66a51388e03bd38e8829e5903ee0389b5f8ce7e39",
  "attempt_id": "EfficientFormer_L3-jinman-coreall-0d86cbbca63b",
  "superseded_attempt_ids": [],
  "sha256": "7b7c1fb28c6b02da867b0d693dd933b19ea009179e57d346efb598ab899b1f54",
  "format": "MXQv7",
  "supported_modes": [
    "single",
    "multi",
    "global4",
    "global8"
  ],
  "size": 34715564,
  "ops_commits": {
    "selection": "e4ebfab8ceddb0367c03deaec499e421df31c5d2"
  },
  "arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/EfficientFormer_L3",
  "publication": {
    "status": "public",
    "reason": "approved"
  }
}