--- library_name: mobilint license: bsd-3-clause pipeline_tag: image-classification tags: - mobilint base_model_relation: quantized --- # EfficientNet_B0_IMAGENET1K_V1 `aries-rb/` holds the MXQ reproduced from the published arxiv folder (https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/EfficientNet_B0_IMAGENET1K_V1). 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 0.76882, top5_accuracy 0.93234. Only the evaluated core mode was measured. SHA-256: `7aa8fcd638cdc642dfd1ccd7d4b3976dbe1a0b09127b9c3c2c7750ebe976f3e8` (7489425 bytes). Verify a download with `sha256sum .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. ```json { "schema_version": 2, "model": "EfficientNet_B0_IMAGENET1K_V1", "variant": "c0923-base", "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": 0.76882 }, "secondary": { "top5_accuracy": 0.93234 }, "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": 98.94977991711498 }, "content_sha256": "04b435fff65c8b464f6aee3ba2112eeb458ad9ec6d9c88fcadf060944894abb5", "attempt_id": "EfficientNet_B0_IMAGENET1K_V1-jinman-coreall-3521b531e76b", "superseded_attempt_ids": [], "sha256": "7aa8fcd638cdc642dfd1ccd7d4b3976dbe1a0b09127b9c3c2c7750ebe976f3e8", "format": "MXQv7", "supported_modes": [ "single", "multi", "global4", "global8" ], "size": 7489425, "ops_commits": { "selection": "417dd6508f5a1f5fce40ca68dbdf1cd0e9e2ccf5" }, "arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/EfficientNet_B0_IMAGENET1K_V1", "publication": { "status": "public", "reason": "approved" } } ```