RegNet_Y_1_6GF.tv2_in1k

RegNet_Y_1_6GF_IMAGENET1K_V2

Source: https://github.com/pytorch/vision

aries-rb/ holds the MXQ reproduced from the published arxiv folder (https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/RegNet_Y_1_6GF_IMAGENET1K_V2). It was compiled by qbcompiler 1.3.0 in the image mobilint/qbcompiler:1.3-cuda12.8.1-ubuntu22.04 (sha256:6ad69aaa9581487ac6a1864b88d4c2179c7a4a486a3ab1ac376dbdfe763415e7) 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 0.80362, top5_accuracy 0.95282. Only the evaluated core mode was measured.

SHA-256: 24e9a47188301d5b33bbb7be82c06fb4c45a296f48cbb34830decb0d23ba2fb0 (51669849 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": "RegNet_Y_1_6GF_IMAGENET1K_V2",
  "variant": "c0923-base",
  "qbcompiler": "1.3.0",
  "qbruntime": "1.5.0",
  "compile": {
    "image_tag": "1.3-cuda12.8.1-ubuntu22.04",
    "image_digest": "sha256:6ad69aaa9581487ac6a1864b88d4c2179c7a4a486a3ab1ac376dbdfe763415e7",
    "inference_scheme": "all",
    "device": "gpu"
  },
  "evaluation": {
    "dataset": "imagenet",
    "sample_count": 50000,
    "primary": {
      "top1_accuracy": 0.80362
    },
    "secondary": {
      "top5_accuracy": 0.95282
    },
    "protocol": null,
    "eval_data_identity": {
      "annotation_sha256": "f00550c10ff1d4110abc683786b6cc09d5082dadd3cee1568f5cfa1dad962960",
      "sample_list_sha256": "54446819dced83110352e5a0361ff05b19c331c5a9802dcb0222e6d1e44a0547"
    },
    "identity_audit": "verified",
    "inference_mode": "async",
    "image_tag": "1.3-cpu-ubuntu22.04",
    "image_digest": "sha256:7c25b894fc0807acdf27f15c61b910b96dc66d3f5d97e04b595b2d7a8008e77c"
  },
  "retention_percent": {
    "top1_accuracy": 99.35463132387122
  },
  "content_sha256": "fe536408c16b936168d1594882d70a5d33268b4e9bc3b0f4d0d6736548e3235f",
  "attempt_id": "RegNet_Y_1_6GF_IMAGENET1K_V2-jinman-coreall-382ed5bbcb4b",
  "superseded_attempt_ids": [],
  "sha256": "24e9a47188301d5b33bbb7be82c06fb4c45a296f48cbb34830decb0d23ba2fb0",
  "format": "MXQv7",
  "supported_modes": [
    "single",
    "multi",
    "global4",
    "global8"
  ],
  "size": 51669849,
  "ops_commits": {
    "selection": "0c7d772cb5d0612e5b906d07ca707e801b5da465"
  },
  "arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/RegNet_Y_1_6GF_IMAGENET1K_V2",
  "publication": {
    "status": "public",
    "reason": "approved"
  }
}