Ultralytics/YOLOv5
object-detection model by Ultralytics
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
[](https://platform.ultralytics.com/?utmsource=huggingface&utmmedium=referral&utmcampaign=platformlaunch&utmcontent=banner&utmterm=ultralyticsgithub) 中文 | 한국어 | 日本語 | Русский | Deutsch | Français | Español | Português | Türkçe | Tiếng Việt | العربية [](https://github.com/ultralytics/ultralytics/actions/workflows/ci.yml) [](https://clickpy.clickhouse.com/dashboard/ultralytics) [](https://discord.com/invite/ultralytics) [](https://community.ultralytics.com/) [](https://www.reddit.com/r/ultralytics/) [](https://console.paperspace.com/github/ultralytics/ultralytics) [](https://colab.research.google.com/github/ultralytics/ultralytics/blob/main/examples/tutorial.ipynb) [](https://www.kaggle.com/models/ultralytics/yolov5) [](https://mybinder.org/v2/gh/ultralytics/ultralytics/HEAD?labpath=examples%2Ftutorial.ipynb) Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models are fast, accurate, and easy to use. They excel at object detection, tracking, instance segmentation, semantic segmentation, image classification, and pose estimation tasks. Find detailed documentation in the Ultralytics Docs. Get support via GitHub Issues. Join discussions on Discord, Reddit, and the Ultralytics Community Forums! Request an Enterprise License for commercial use at Ultralytics Licensing. See below for quickstart installation and usage examples. For comprehensive guidance on training, validation, prediction, and deployment, refer to our full Ultralytics…
Read the full model card ↗ · Preview checked 2026-09-21T06:40:41.791Z
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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
Ultralytics/YOLOv5 is a object-detection model repository published by Ultralytics 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)
- 1,358
- Cumulative likes
- 9
- Hugging Face trending score
- 0
- Reported safetensors parameters
- Not reported
- Architecture
- Not reported
- License
- agpl-3.0
- Access
- Not gated by Hugging Face
- Created
- 2024-11-14T09:33:32.000Z
- Last modified
- 2026-06-26T10:23:02.000Z
Compatibility and lineage
Reported languages: en, zh, ja, ru, de, fr, es, pt, tr, vi, ar
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
Check license terms and access requirements first. Review the model card’s documented loading instructions, evaluations and safety limitations. Benchmark scores are not imported by this directory, and popularity is not an accuracy ranking.
No model weights are downloaded or executed by AltAPIs. Never enable remote model code without reviewing it.
Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-09-21T06:36:53.017Z. 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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