TinyFormer-X-PBM detection weights, repackaged for LibreYOLO.
TinyFormer ("TinyFormer: Preserving Tiny Objects in YOLO-DETR Hybrid
Real-time Detectors", arXiv:2605.25046) is a DEIMv2-derived YOLO-DETR hybrid
specialised for tiny objects via a Spatial Semantic Adapter and a 4-scale
Parallel Bi-fusion neck. This size runs on a finetuned DINOv3 ViT-S/16+ tower.
1from libreyolo import LibreYOLO
2
3model = LibreYOLO("LibreTinyFormerx.pt") # auto-downloads from this repo
4results = model.predict("image.jpg")
Derived from
mmpmmpmmpjosh/TinyFormer
at commit
9075d9f,
sourced from the official
Google Drive checkpoint mirror.
Copyright (C) 2026 AICVlab, National Yang Ming Chiao Tung University (NYCU).
The TinyFormer codebase is licensed under the Apache License, Version 2.0
(DEIM/DEIMv2 lineage).
The backbone parameters derive from
facebookresearch/dinov3
(a finetuned DINOv3 ViT-S/16+ tower) and are licensed under the
DINOv3 License.
Because this checkpoint bundles DINOv3-derived parameters, the combined
distribution is governed by the terms of both licenses.
Checkpoint metadata wrapping only — learned parameters are unchanged (the EMA
weights of the released solver checkpoint). The wrapper adds
model_family,
size,
nc, and
names fields so the unified
LibreYOLO() factory
routes correctly without filename heuristics.
See
weights/convert_tinyformer_weights.py in the
LibreYOLO source repository.
Dual-licensed: Apache License 2.0 (TinyFormer/DEIMv2 components) and the
DINOv3 License (backbone parameters). The combined LICENSE file in this
repository contains both license texts. See also
NOTICE for
attribution detail.
