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Custom Serializer for Table Enrichment

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Signed-off-by: Nikhil Khandelwal <nikhil.khandelwal3@ibm.com>
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Nikhil Khandelwal 2025-05-15 00:36:55 +05:30
parent 25856e1392
commit fab016226f
1 changed files with 5 additions and 3 deletions
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8
docs/examples/serialization.ipynb
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@ -434,7 +434,7 @@
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@ -479,7 +479,7 @@
}, },
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@ -546,7 +546,7 @@
}, },
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"outputs": [ "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", "│ 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", "│ │\n",
"│ Figure 1: System architecture: Simplified sketch of document question-answering pipeline. │\n", "│ Figure 1: System architecture: Simplified sketch of document question-answering pipeline. │\n",
"│ #/pictures/0 │\n",
"│ &lt;!-- 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", "│ &lt;!-- 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", "│ 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. --&gt; │\n", "│ generation step involves generating a response from the information retrieval step. --&gt; │\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", "│ 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", "│ │\n",
"│ Figure 1: System architecture: Simplified sketch of document question-answering pipeline. │\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", "│ <!-- 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", "│ 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", "│ generation step involves generating a response from the information retrieval step. --> │\n",