diff --git a/docs/en/hub/datasets.md b/docs/en/hub/datasets.md
index 1ab7c45f..40cc207e 100644
--- a/docs/en/hub/datasets.md
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@@ -10,6 +10,17 @@ keywords: Ultralytics, HUB datasets, YOLO model training, upload datasets, datas
Once uploaded, datasets can be immediately utilized for model training. This integrated approach facilitates a seamless transition from dataset management to model training, significantly simplifying the entire process.
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+ Watch: Watch: Upload Datasets to Ultralytics HUB | Complete Walkthrough of Dataset Upload Feature
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## Upload Dataset
Ultralytics HUB datasets are just like YOLOv5 and YOLOv8 🚀 datasets. They use the same structure and the same label formats to keep everything simple.
diff --git a/docs/en/integrations/coreml.md b/docs/en/integrations/coreml.md
index 45aa8a28..cbcff691 100644
--- a/docs/en/integrations/coreml.md
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@@ -13,7 +13,7 @@ The CoreML export format allows you to optimize your [Ultralytics YOLOv8](https:
## CoreML
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[CoreML](https://developer.apple.com/documentation/coreml) is Apple's foundational machine learning framework that builds upon Accelerate, BNNS, and Metal Performance Shaders. It provides a machine-learning model format that seamlessly integrates into iOS applications and supports tasks such as image analysis, natural language processing, audio-to-text conversion, and sound analysis.
diff --git a/docs/en/integrations/gradio.md b/docs/en/integrations/gradio.md
index ce67ca5a..3845b4f1 100644
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* **Real-Time Adjustments:** Parameters such as confidence and IoU thresholds can be adjusted on the fly, allowing for immediate feedback and optimization of detection results.
* **Broad Accessibility:** The Gradio web interface can be accessed by anyone, making it an excellent tool for demonstrations, educational purposes, and quick experiments.
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