Update main.css

content/post/fine-tuning-a-mystical-assistant-with-llama-3-and-unsloth.markdown

@@ -38,7 +38,7 @@ from bs4 import BeautifulSoup
 import logging
 from datasets import load_dataset
 
-logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
 
 BASE_URL = "https://sacred-texts.com/eso/sta/sta{:02d}.htm"
 OUTPUT_DIR = "secret_teachings_content"
@@ -48,27 +48,27 @@ NUM_PAGES = 50
 def fetch_and_save_content(url, filename):
     if os.path.exists(filename):
         logging.info(f"File {filename} already exists, skipping download")
-        with open(filename, 'r', encoding='utf-8') as f:
+        with open(filename, "r", encoding="utf-8") as f:
             return f.read()
 
     logging.info(f"Fetching content from {url}")
     response = requests.get(url)
     response.raise_for_status()
 
     content = response.text
-    with open(filename, 'w', encoding='utf-8') as f:
+    with open(filename, "w", encoding="utf-8") as f:
         f.write(content)
 
     return content
 
 def parse_content(html_content):
-    soup = BeautifulSoup(html_content, 'html.parser')
-    paragraphs = soup.find_all('p')
+    soup = BeautifulSoup(html_content, "html.parser")
+    paragraphs = soup.find_all("p")
     return [p.get_text().strip() for p in paragraphs if p.get_text().strip()]
 
 def split_paragraph(paragraph):
-    sentences = paragraph.split('. ')
-    return [s.strip() + '.' for s in sentences if s.strip()]
+    sentences = paragraph.split(". ")
+    return [s.strip() + "." for s in sentences if s.strip()]
 
 def generate_conversation(paragraph):
     sentences = split_paragraph(paragraph)
@@ -89,7 +89,7 @@ def generate_training_data(content_dir):
     conversations = []
     for filename in os.listdir(content_dir):
         if filename.endswith(".html"):
-            with open(os.path.join(content_dir, filename), 'r', encoding='utf-8') as f:
+            with open(os.path.join(content_dir, filename), "r", encoding="utf-8") as f:
                 content = f.read()
             paragraphs = parse_content(content)
             for paragraph in paragraphs:
@@ -111,7 +111,7 @@ def main():
     training_data = generate_training_data(OUTPUT_DIR)
 
     logging.info(f"Saving training data to {JSON_OUTPUT}")
-    with open(JSON_OUTPUT, 'w', encoding='utf-8') as f:
+    with open(JSON_OUTPUT, "w", encoding="utf-8") as f:
         json.dump(training_data, f, ensure_ascii=False, indent=2)
 
     logging.info("Process completed successfully")
@@ -262,4 +262,4 @@ Hopefully this is helpful to some other people doing LLM fine tuning at home.
 
 Until next time, stay sassy Internet.
 
-* N
+* N

static/stylesheets/main.css

@@ -20,7 +20,8 @@ body {
     padding: 0;
     border-top: 8px solid #333;
     font-family: "Lato", sans-serif;
-    font-size: 16px;
+    font-size: 20px;
+    line-height: 32px;
     color: #333;
 }
 
@@ -36,7 +37,8 @@ body {
         width: 90%;
     }
     article {
-        font-size: 18px !important;
+        font-size: 20px !important;
+        line-height: 32px !important;
     }
 }
 
@@ -53,21 +55,6 @@ pre {
 
 }
 
-h1 {
-    margin-top: 0.9em;
-    font-size: 1.3em;
-    font-weight: normal;
-    font-style: normal;
-    text-align: center;
-}
-
-h2 {
-    margin-top: 0.9em;
-    font-size: 1em;
-    font-weight: bold;
-    font-style: normal;
-}
-
 .wrap>footer {
     margin-top: 2em;
     padding: 2em 0;
@@ -178,14 +165,6 @@ article header {
     text-align: center;
 }
 
-article header h1 {
-    font-size: 1.5em;
-    font-weight: bold;
-    font-style: normal;
-    line-height: 1em;
-    text-align: center;
-}
-
 article header time {
     font-size: 0.9em;
     font-style: normal;
@@ -200,9 +179,11 @@ article hr {
 }
 
 #content img {
-    max-width: 100%;
-    margin: 4px auto;
-    display: block;
+  max-width: 100%;
+  max-height: 512px;
+  margin: 4px auto;
+  display: block;
+  height: auto;
 }
 
 article p .word1,article p .word2,article p .word3 {
@@ -328,11 +309,14 @@ iframe {
 }
 
 div#content {
-    margin: 0% 26%; /* default margin for larger screens */
+    margin: 0% 12%; /* default margin for larger screens */
 }
 
 @media only screen and (max-width: 767px) {
   /* small screens */
+  #wrap {
+    padding: 0px 10px;
+  }
   div#content {
     margin: 0% 5px; /* 5px margin on small screens */
   }
@@ -389,10 +373,6 @@ li.title {
     text-align: left;
 }
 
-h1,h2,h3,h4,h5,h6 {
-    font-weight: bold;
-}
-
 input#reader-email {
     border-radius: 5px;
     width: 80%;
@@ -753,3 +733,12 @@ input#archive-search {
   display: block;
   width: 200px;
 }
+
+p > code {
+  border-radius: 6px;
+  padding: 1px;
+  margin: 1px;
+  color: rgb(31, 35, 40, 0.9);
+  background-color: rgba(175, 184, 193, 0.2);
+  border: 1px solid rgb(31, 35, 40);
+}