jameslahm/yoloe
object-detection model by jameslahm
From the publisher
Model card & documentation
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Official PyTorch implementation of YOLOE. Comparison of performance, training cost, and inference efficiency between YOLOE (Ours) and YOLO-Worldv2 in terms of open text prompts. YOLOE: Real-Time Seeing Anything.\ Ao Wang, Lihao Liu, Hui Chen, Zijia Lin, Jungong Han, and Guiguang Ding\ [](https://arxiv.org/abs/2503.07465) [](https://huggingface.co/jameslahm/yoloe/tree/main) [](https://huggingface.co/spaces/jameslahm/yoloe) We introduce YOLOE(ye), a highly efficient, unified, and open object detection and segmentation model, like human eye, under different prompt mechanisms, like texts, visual inputs, and prompt-free paradigm. Abstract Object detection and segmentation are widely employed in computer vision applications, yet conventional models like YOLO series, while efficient and accurate, are limited by predefined categories, hindering adaptability in open scenarios. Recent open-set methods leverage text prompts, visual cues, or prompt-free paradigm to overcome this, but often compromise between performance and efficiency due to high computational demands or deployment complexity. In this work, we introduce YOLOE, which integrates detection and segmentation across diverse open prompt mechanisms within…
Read the full model card ↗ · Preview checked 2026-10-28T03:18:54.973Z
Inside the original model card — Document outline
- YOLOE: Real-Time Seeing Anything
- Performance
- Zero-shot detection evaluation
- Zero-shot segmentation evaluation
- Prompt-free evaluation
- Downstream transfer on COCO
- Installation
- Demo
- Prediction
- Text prompt
- Visual prompt
- Prompt free
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Documentation belongs to its respective authors. Reported project/model license: agpl-3.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
jameslahm/yoloe is a object-detection model repository published by jameslahm on Hugging Face. The source reports the ultralytics library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- object-detection
- Library
- ultralytics
- Recent downloads (30 days)
- 8,771
- Cumulative likes
- 44
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- agpl-3.0
- Access
- Not gated by Hugging Face
- Created
- 2025-03-10T07:54:02.000Z
- Last modified
- 2025-03-30T13:45:19.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:34.007Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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