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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 <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.
```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"
}
}
```
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