Deployed 82c16db with MkDocs version: 1.5.3

creating_embeddings/index.html

@@ -127,7 +127,7 @@ <h3 id="creating-embeddings">Creating embeddings</h3>
 <p>Parse csv to text</p>
 <pre><code>python -m document_parsing.parse_csv_to_text
 </code></pre>
-<p>Parse the documents with </p>
+<p>Parse the documents with. The new document parsing uses multiprocess to parse metadata keys created with parse_ner script. This increases the processing speed with large key files by a significant margin. The old script uses a single thread for processing keys and this can cause significant slowdown with many documents with large keyfiles. You can give the number of threads for the multiprocess with --threads</p>
 <pre><code>python -m document_parsing.parse_text_documents
 python -m document_parsing.parse_text_documents
 python -m document_parsing.parse_json_documents

index.html

@@ -161,5 +161,5 @@ <h1 id="llama-cpp-chat-memory">llama-cpp-chat-memory</h1>
 
 <!--
 MkDocs version : 1.5.3
-Build Date UTC : 2024-04-15 14:41:04.895639+00:00
+Build Date UTC : 2024-04-21 06:17:30.084241+00:00
 -->

sitemap.xml

@@ -2,67 +2,67 @@
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+         <lastmod>2024-04-21</lastmod>
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          <loc>https://ossirytk.github.io/llama-cpp-chat-memory/configs/</loc>
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     <url>
          <loc>https://ossirytk.github.io/llama-cpp-chat-memory/getting_started/</loc>
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+         <lastmod>2024-04-21</lastmod>
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     <url>
          <loc>https://ossirytk.github.io/llama-cpp-chat-memory/named_entity_recognition/</loc>
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     <url>
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