ViT_Base_Patch32_CLIP_448

Source: https://github.com/huggingface/pytorch-image-models

aries-rb/ holds the MXQ reproduced from the published arxiv folder (https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/ViT_Base_Patch32_CLIP_448). 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 0.85712, top5_accuracy 0.97588. Only the evaluated core mode was measured.

SHA-256: b895d901fc8ec278748af34c7d38e8180a19a4d4aaf814c77f3df4004074f3a7 (106389236 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": "ViT_Base_Patch32_CLIP_448",
  "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": 0.85712
    },
    "secondary": {
      "top5_accuracy": 0.97588
    },
    "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": 99.90675121223424
  },
  "content_sha256": "6b538ccdcecf3f1d21c6229e8706cd02c08f1b895334114acf343ff5a87609b7",
  "attempt_id": "ViT_Base_Patch32_CLIP_448-jinman-coreall-13905b06de74",
  "superseded_attempt_ids": [],
  "sha256": "b895d901fc8ec278748af34c7d38e8180a19a4d4aaf814c77f3df4004074f3a7",
  "format": "MXQv7",
  "supported_modes": [
    "single",
    "multi",
    "global4",
    "global8"
  ],
  "size": 106389236,
  "ops_commits": {
    "selection": "0c7d772cb5d0612e5b906d07ca707e801b5da465"
  },
  "arxiv_folder": "https://github.com/mobilint/mblt-model-arxiv/tree/main/models/image_classification/ViT_Base_Patch32_CLIP_448",
  "publication": {
    "status": "public",
    "reason": "approved"
  }
}
Downloads last month
23
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support

Model tree for mobilint/ViT_Base_Patch32_CLIP_448

Quantized
(1)
this model