From e2986ca59c90e2b9dc1a2fb2b386720f8ed31e0b Mon Sep 17 00:00:00 2001
From: Jean-Luc Parouty <Jean-Luc.Parouty@grenoble-inp.fr>
Date: Wed, 19 Feb 2020 09:39:39 +0100
Subject: [PATCH] test gitlab/jupyter/markdown bug image

Former-commit-id: 00ba2083c4d486b135989f4beddbf4db15dd4ad5
---
 BHPD/01-DNN-Regression.ipynb | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/BHPD/01-DNN-Regression.ipynb b/BHPD/01-DNN-Regression.ipynb
index 64e2b61..6406040 100644
--- a/BHPD/01-DNN-Regression.ipynb
+++ b/BHPD/01-DNN-Regression.ipynb
@@ -4,8 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "![Fidle](../fidle/img/00-Fidle-header-01.png)\n",
-    "![Fidle](00-Fidle-header-01.png)\n",
+    "![Hello World](data:image/png;base64,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)\n",
     "\n",
     "# Deep Neural Network (DNN) - BHPD dataset\n",
     "\n",
-- 
GitLab