Instructions to use apus-ailab/APUS-Reflex with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use apus-ailab/APUS-Reflex with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("apus-ailab/APUS-Reflex", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 4,501 Bytes
68e5880 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 | {
"title": "APUS-OpenJev-v1",
"created_date": "2026-09-21",
"panel": {
"records": 80,
"parent_groups": 79,
"task_counts": {
"Browser": 16,
"HelpSteer3": 16,
"BoolQ": 16,
"MNLI": 16,
"Score": 16
},
"score_labels": "16 No, 0 Yes",
"split": "validation/development regression; not sealed final",
"laya_export_sha256": "26aa47e8f56c18a403eb4c8379d5cccb9cea5af97c191ab26ec36b8fb17ae923"
},
"accuracy": [
{
"model": "APUS-OpenJev 9B",
"correct": 68,
"total": 80,
"percentage": 85.0,
"source": "merged9b",
"effort": "high",
"variant_directory": "9B-3000"
},
{
"model": "APUS-OpenJev 4B",
"correct": 66,
"total": 80,
"percentage": 82.5,
"source": "merged4b",
"effort": "high",
"variant_directory": "4B-5949"
},
{
"model": "Jev official API",
"correct": 66,
"total": 80,
"percentage": 82.5,
"source": "native9b_latency"
},
{
"model": "Laya typed / full input",
"correct": 55,
"total": 80,
"percentage": 68.75,
"source": "laya_repeats",
"config": "typed-fullinput",
"repetitions": 3,
"identical_accuracy": true,
"truncations": 0
}
],
"latency": {
"native_forward_historical": [
{
"model": "APUS-OpenJev 9B",
"p50_ms": 77.76357303373516,
"p95_ms": 505.1563191227615,
"source": "native9b_latency"
},
{
"model": "APUS-OpenJev 4B",
"p50_ms": 85.43,
"p95_ms": 406.3,
"source": "native4b_latency"
}
],
"laya_local_system_one": {
"model": "Laya typed / full input",
"p50_ms": 8.684632601216435,
"p95_ms": 37.65514073893428,
"p50_range_ms": [
8.429150097072124,
8.730278117582202
],
"p95_range_ms": [
37.441988941282034,
37.88864379748702
],
"aggregation": "median of three per-run P50 and P95 values; not pooled or fastest-run selection",
"scope": "native system_one includes tokenization, transfer, forward and structured response; excludes HTTP and loading",
"source": "laya_repeats"
},
"official_http": {
"model": "Jev official API",
"p50_ms": 436.9597500190139,
"p95_ms": 4874.612333020195,
"scope": "remote full HTTP response including network/queue/service; not client-observable TTFT",
"source": "native9b_latency"
},
"cross_scope_speedup_claim": false,
"merged_package_latency_retest": false
},
"sources": {
"laya_repeats": {
"project_relative_path": "docs/feat-jev-combined/evidence/laya-repeated-20260921/summary.json",
"sha256": "16a2d3a265909e40f65cdb9331417a6d46a1f2140759f94d2b183728d64825e6"
},
"native9b_latency": {
"project_relative_path": "docs/feat-jev-combined/evidence/9b-checkpoints80/3000/report.json",
"sha256": "f3b93d04ab8e99d3cf135d410b559e1c96e980fba43c59b71428fe8c815b9303"
},
"native4b_latency": {
"project_relative_path": "docs/feat-jev-combined/official-typesafe-vs-final5949-80-20260920.md",
"sha256": "5a7568a998d4be13555374399aa91e9b458d782336b14ab33603a2ebcabe99fc"
},
"merged4b": {
"project_relative_path": "docs/feat-jev-combined/openjet-release-20260921/merged-release/evidence/4B/comparison.json",
"sha256": "97cc94ddebb4f321d3d4ed29c89a0d8b1b3d6570e48bff427c635ba82f67862e"
},
"merged9b": {
"project_relative_path": "docs/feat-jev-combined/openjet-release-20260921/merged-release/evidence/9B/comparison.json",
"sha256": "d2ea8a7af10f09fdfde166384ffb18fb5a19ebf1a1281c58cb72806a45878c41"
},
"panel_description": {
"project_relative_path": "docs/feat-jev-combined/openjet-release-20260921/eval-dataset/SPLIT_AND_EVALUATION.md",
"sha256": "b14b8af51f0527443b369f6995d46b786207dbf663ef2ce5afc9cc0a02d31b8b"
}
},
"limitations": [
"80 development questions are reused and have influenced development/version selection.",
"Two more correct answers than Jev does not establish significant superiority or noninferiority.",
"Score is all No; Browser is static candidate selection, not website completion.",
"Laya full-input formatting was changed without retraining; three repeats do not increase independent sample size.",
"Historical native forward, local system_one and remote HTTP are different timing boundaries."
]
}
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