From fa10713ca848d0bcda0121b8db693ad445b21fdb Mon Sep 17 00:00:00 2001 From: afondiel Date: Tue, 30 Jul 2024 21:55:32 +0200 Subject: [PATCH] L3: update --- L3_object_detection_notes.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/L3_object_detection_notes.md b/L3_object_detection_notes.md index cc34e31..39cc10b 100644 --- a/L3_object_detection_notes.md +++ b/L3_object_detection_notes.md @@ -63,7 +63,7 @@ While in the **pre-training phase**, the model was just learning how to associat During the **fine tuning stage**, the model learns to `identify, object and associate them with a particular word or string` -## Lab: Hands-On Notebook 👉 [![Open notebook in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/afondiel/Prompt-Engineering-for-Vision-Models-DeepLearningAI/blob/main/lab/notebooks/L3_Object_Detection.ipynb) +## Lab: Hands-On Notebook 👉 [![Open notebook in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/afondiel/Prompt-Engineering-for-Vision-Models-DeepLearningAI/blob/main/lab/notebooks/L3/L3_Object_Detection.ipynb) Now that we have covered at a high level how the OWL-ViT model works, let's jump into some code and see how we can use it in practice