From ac5bd970829a139b1c161b74eb6d66f20a46af68 Mon Sep 17 00:00:00 2001
From: Shishir Patil <shishirpatil@berkeley.edu>
Date: Tue, 28 Nov 2023 17:58:46 +0530
Subject: [PATCH] Fixing link to RAT, and minor mods to OpenFunctions

---
 blog.html                   | 2 +-
 blogs/4_open_functions.html | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/blog.html b/blog.html
index d79f0c4f7..ad3e7a1e9 100644
--- a/blog.html
+++ b/blog.html
@@ -285,7 +285,7 @@ <h2 class="blog-title">Reality Bytes: How to Measure Hallucinations in LLMs</h2>
     
         <!-- Blog Post 3 -->
         <div class="blog-post">
-            <a href="blogs/3_retriever_ware_training.html">
+            <a href="blogs/3_retriever_aware_training.html">
                 <div class="blog-content">
                     <h2 class="blog-title">Retriever-Aware Training (RAT): Are LLMs memorizing or understanding?</h2>
                     <div class="author-date">
diff --git a/blogs/4_open_functions.html b/blogs/4_open_functions.html
index 23b31a73a..d0dd643e1 100644
--- a/blogs/4_open_functions.html
+++ b/blogs/4_open_functions.html
@@ -97,7 +97,7 @@ <h2 class="blog-title">Gorilla OpenFunctions</h2>
                         <ul>
                             <li>Colab Notebook: <a href="https://colab.research.google.com/drive/16M5J2H9F8YQora_W2PDnp120slZH-Mqd?usp=sharing">OpenFunctions</a></li>
                             <li>Dataset: <a href="https://github.com/ShishirPatil/gorilla/tree/main/openfunctions">GitHub</a></li>
-                            <li>Models on HuggingFace: <a href="https://huggingface.co/gorilla-llm/gorilla-openfunctions-v1">gorilla-llm/gorilla-openfunctions-v1</a></li>
+                            <li>Models on HuggingFace: <a href="https://huggingface.co/gorilla-llm/gorilla-openfunctions-v0">gorilla-llm/gorilla-openfunctions-v0</a></li>
                         </ul>
                     </p>
                 </div>
@@ -214,7 +214,7 @@ <h4 id="benchmarking">OpenFunctions Performance Benchmarking</h4>
                         </i>
                         <br>
                     <p> When calling to OpenAI's function calling models, if the required parameters are not supplied within the instruction, this leads the function calling models to output "follow-up" questions requesting the required parameters. This results in "incomplete" status as displayed in above graph. 
-                        We treat "incomplete" execution as "success" during our accuracy calculation because the model recognized the missing parameters successfully. 
+                        We treat "incomplete" execution as "success" during our accuracy calculation because the model recognized the missing parameters successfully. Note that this is consistent across all evaluations. 
                         Our OpenFunctions model, as well as regular GPT-4, due to its chat completion nature, will fill up the required parameters with placeholders or default values, allowing undisturbed generation. </p>
 
                 </div>