Initial upload

LICENSE

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+===== TinyFormer (Apache License 2.0) =====
+
+Copyright (C) 2026 AICVlab, National Yang Ming Chiao Tung University (NYCU).
+Copyright (C) INTELLINDUST INFORMATION TECHNOLOGY (SHENZHEN) CO., LTD. and all its affiliates.  
+
+DEIM is licensed under the Apache License. 
+
+A copy of the Apache License License is included in this file.
+
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+===== DINOv3 License =====
+
+# DINOv3 License
+
+*Last Updated: August 19, 2025*
+
+**“Agreement”** means the terms and conditions for use, reproduction, distribution and modification of the DINO Materials set forth herein.
+
+**“DINO Materials”** means, collectively, Documentation and the models, software and algorithms, including machine-learning model code, trained model weights, inference-enabling code, training-enabling code, fine-tuning enabling code, and other elements of the foregoing distributed by Meta and made available under this Agreement.
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+By clicking “I Accept” below or by using or distributing any portion or element of the DINO Materials, you agree to be bound by this Agreement.
+
+## 1. License Rights and Redistribution.
+
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+
+## 2. User Support.
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+
+## 3. Disclaimer of Warranty.
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LibreTinyFormerl.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:d5cd03a898863aaf9d35fc30176b3b0ae228051e6fabca377e13a5e1d790dd25
+size 136193104

LibreTinyFormerl.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1335399aac84965c9a15edb75a90210f5ba98a0a256966ceb6076544c4d88b27
+size 136576845

NOTICE

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+LibreTinyFormer weights
+-----------------------
+
+This product contains weights derived from TinyFormer
+(https://github.com/mmpmmpmmpjosh/TinyFormer).
+Copyright (C) 2026 AICVlab, National Yang Ming Chiao Tung University (NYCU).
+Licensed under the Apache License, Version 2.0.
+TinyFormer builds on DEIMv2 (https://github.com/Intellindust-AI-Lab/DEIMv2),
+Copyright (C) Intellindust Information Technology (Shenzhen) Co., Ltd.,
+also licensed under the Apache License, Version 2.0.
+
+The backbone parameters in this checkpoint are derived from DINOv3
+(https://github.com/facebookresearch/dinov3).
+Copyright (c) Meta Platforms, Inc. and affiliates.
+Licensed under the DINOv3 License
+(https://ai.meta.com/resources/models-and-libraries/dinov3-license/).
+The DINOv3 license text is included alongside the Apache License in the
+LICENSE file in this repository.

README.md

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+---
+license: other
+license_name: tinyformer-dinov3
+license_link: LICENSE
+library_name: libreyolo
+tags:
+  - object-detection
+  - tinyformer
+---
+
+# LibreTinyFormerl
+
+TinyFormer-L-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.
+
+Reported COCO val2017 mAP50-95: **56.8**.
+
+## Usage
+
+```python
+from libreyolo import LibreYOLO
+
+model = LibreYOLO("LibreTinyFormerl.pt")   # auto-downloads from this repo
+results = model.predict("image.jpg")
+```
+
+## Source
+
+Derived from [mmpmmpmmpjosh/TinyFormer](https://github.com/mmpmmpmmpjosh/TinyFormer)
+at commit [`9075d9f`](https://github.com/mmpmmpmmpjosh/TinyFormer/commit/9075d9fdf5ce989ca3c7e830a780dfc7fbbe4ec1),
+sourced from the official [Google Drive checkpoint mirror](https://drive.google.com/drive/folders/1yIsUO14g5EyTFRbDeISoNJSDqNeSgT5o).
+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](https://github.com/facebookresearch/dinov3)
+(a finetuned DINOv3 ViT-S/16 tower) and are licensed under the
+[DINOv3 License](https://ai.meta.com/resources/models-and-libraries/dinov3-license/).
+Because this checkpoint bundles DINOv3-derived parameters, the combined
+distribution is governed by the terms of both licenses.
+
+## Modifications
+
+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](https://github.com/LibreYOLO/libreyolo).
+
+## License
+
+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`](./NOTICE) for
+attribution detail.