From fab016226f8eb8a707ab8c961251910bb9e9e22b Mon Sep 17 00:00:00 2001 From: Nikhil Khandelwal Date: Thu, 15 May 2025 00:36:55 +0530 Subject: [PATCH] Custom Serializer for Table Enrichment Signed-off-by: Nikhil Khandelwal --- docs/examples/serialization.ipynb | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/docs/examples/serialization.ipynb b/docs/examples/serialization.ipynb index d297a78a..38bfe003 100644 --- a/docs/examples/serialization.ipynb +++ b/docs/examples/serialization.ipynb @@ -434,7 +434,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -479,7 +479,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -546,7 +546,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -581,6 +581,7 @@ "│ Imagebased methods usually employ Transformer or CNN architectures on the images of pages (Zhang et al. 2023; Li et al. 2022; Huang et al. 2022). On the other hand, deep learning- │\n", "│ │\n", "│ Figure 1: System architecture: Simplified sketch of document question-answering pipeline. │\n", + "│ #/pictures/0 │\n", "│ <!-- Picture description: The image depicts a document conversion process. It is a sequence of steps that includes document conversion, information retrieval, and response generation. The document │\n", "│ conversion step involves converting the document from a text format to a markdown format. The information retrieval step involves retrieving the document from a database or other source. The response │\n", "│ generation step involves generating a response from the information retrieval step. --> │\n", @@ -621,6 +622,7 @@ "│ Imagebased methods usually employ Transformer or CNN architectures on the images of pages (Zhang et al. 2023; Li et al. 2022; Huang et al. 2022). On the other hand, deep learning- │\n", "│ │\n", "│ Figure 1: System architecture: Simplified sketch of document question-answering pipeline. │\n", + "│ #/pictures/0 │\n", "│ │\n",