Instructions to use oliver0804/LocateAnything-3B-RK3588 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- RKLLM
How to use oliver0804/LocateAnything-3B-RK3588 with RKLLM:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
File size: 1,515 Bytes
0522016 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | This repository contains files converted from nvidia/LocateAnything-3B (https://huggingface.co/nvidia/LocateAnything-3B).
LocateAnything-3B is Copyright (c) 2026, NVIDIA CORPORATION, and is licensed under the NVIDIA License (see LICENSE).
Use is limited to non-commercial research or evaluation purposes. Commercial use is not permitted, except by NVIDIA
Corporation and its affiliates. The converted weights and the code in this repository are derivative works of that
Work and are distributed under the same license; no additional terms ("Your Terms") are applied.
Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) Alibaba Cloud. All Rights Reserved.
(The language model of LocateAnything-3B is Qwen2.5-3B-Instruct; see LICENSE-Qwen.)
Vision encoder: MoonViT-SO-400M by Moonshot AI, released under the MIT License as declared on its model card
(https://huggingface.co/moonshotai/MoonViT-SO-400M). The upstream repository does not include a LICENSE file or a
named copyright holder.
Built with Qwen.
Modifications: the model weights were extracted, converted and quantized (language model: RKLLM w8a8; vision encoder
plus projector: RKNN fp16, fixed 448x448 input) for the Rockchip RK3588 NPU. The Python files under rk3588/ and tools/
were written or modified for this conversion; portions are ported from NVIDIA's generate_utils.py,
modeling_locateanything.py and modeling_vit.py.
COCO val2017 annotations (CC BY 4.0, https://cocodataset.org) were used to build eval/eval_set.json.
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