📚 Auto-publish: Add/update 3 blog posts

Generated on: Sun Aug 3 02:45:17 UTC 2025 Source: md-personal repository
2025-08-03 02:45:17 +00:00
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--- a/content/posts/a-deep-dive-into-ppo-for-language-models.md
+++ b/content/posts/a-deep-dive-into-ppo-for-language-models.md
@@ -1,6 +1,6 @@
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 title: "A Deep Dive into PPO for Language Models"
-date: 2025-08-03T02:36:44
+date: 2025-08-03T02:45:10
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@@ -9,7 +9,7 @@ Large Language Models (LLMs) have demonstrated astonishing capabilities, but out

 You may have seen diagrams like the one below, which outlines the RLHF training process. It can look intimidating, with a web of interconnected models, losses, and data flows.

-![[Pasted image 20250730232756.png]]
+![](/images/a-deep-dive-into-ppo-for-language-models/.png)

 This post will decode that diagram, piece by piece. We'll explore the "why" behind each component, moving from high-level concepts to the deep technical reasoning that makes this process work.

--- a/content/posts/t5-the-transformer-that-zigged-when-others-zagged-an-architectural-deep-dive.md
+++ b/content/posts/t5-the-transformer-that-zigged-when-others-zagged-an-architectural-deep-dive.md
@@ -1,6 +1,6 @@
 ---
 title: "T5 - The Transformer That Zigged When Others Zagged - An Architectural Deep Dive"
-date: 2025-08-03T02:36:44
+date: 2025-08-03T02:45:10
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--- a/static/images/a-deep-dive-into-ppo-for-language-models/.png
+++ b/static/images/a-deep-dive-into-ppo-for-language-models/.png