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DeusImperator
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L3.3-GeneticLemonade-Unleashed-v3-70B_exl3_3.0bpw_H6

Text Generation
Transformers
Safetensors
llama
conversational
text-generation-inference
3-bit
exl3
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  1. .gitattributes +1 -0
  2. README.md +451 -0
  3. config.json +46 -0
  4. generation_config.json +12 -0
  5. huggingface-metadata.txt +35 -0
  6. model-00001-of-00007.safetensors +3 -0
  7. model-00002-of-00007.safetensors +3 -0
  8. model-00003-of-00007.safetensors +3 -0
  9. model-00004-of-00007.safetensors +3 -0
  10. model-00005-of-00007.safetensors +3 -0
  11. model-00006-of-00007.safetensors +3 -0
  12. model-00007-of-00007.safetensors +3 -0
  13. model.safetensors.index.json +0 -0
  14. quantization_config.json +0 -0
  15. special_tokens_map.json +23 -0
  16. tokenizer.json +3 -0
  17. tokenizer_config.json +2064 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ base_model:
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+ - zerofata/L3.3-GeneticLemonade-Unleashed-v3-70B
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+ library_name: transformers
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+ license: llama3
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+ ---
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+
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+ # L3.3-GeneticLemonade-Unleashed-v3-70B - EXL3 3.0bpw H6
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+
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+ This is a 3bpw EXL3 quant of [zerofata/L3.3-GeneticLemonade-Unleashed-v3-70B](https://huggingface.co/zerofata/L3.3-GeneticLemonade-Unleashed-v3-70B)
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+
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+ This quant was made using exllamav3-0.0.3
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+
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+ 3bpw fits in 32GB VRAM on Windows with around 18-20k Q8 context (tested in tabbyAPI)
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+
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+ I tested this quant shortly in some random RPs (including ones over 8k and 16k context) and it seems to work fine
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+
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+ ## Prompt Templates
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+
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+ Uses Llama 3 Instruct format.
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+
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+ ### Original readme below
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+
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+ ---
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+
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+ <!DOCTYPE html>
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+ <style>
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+ /* Base styling for cyberpunk theme */
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+ body {font-family: sans-serif; background-color: #080c14; color: #e1e9f0; line-height: 1.6; margin: 0; padding: 0;}
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+
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+ .lemonade-text {
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+ color: #33ff99;
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+ position: relative; /* Keep relative positioning */
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+ z-index: 2;
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+ margin-left: 0.2em;
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+ text-shadow: 0 0 10px #33ff99; /* Add static glow */
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+ }
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+
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+ /* Section styling */
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+ .section-container {background-color: rgba(8, 12, 20, 0.7); margin-bottom: 30px; position: relative; overflow: hidden; border-bottom: 1px solid #33ff99;}
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+ .section-header {display: flex; align-items: center; background-color: rgba(0, 195, 255, 0.1); padding: 10px 20px;}
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+ .section-indicator {width: 8px; height: 20px; background-color: #33ff99; margin-right: 15px;}
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+ .section-title {font-family: 'Orbitron', sans-serif; color: #e1e9f0; font-size: 1.3rem; margin: 0; letter-spacing: 2px; text-transform: uppercase; font-weight: 500;}
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+ .section-content {padding: 20px; font-family: sans-serif; color: #e1e9f0; line-height: 1.6;}
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+
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+ /* Title styling */
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+ .title-container {
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+ background-color: #080c14;
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+ position: relative;
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+ overflow: hidden;
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+ margin-bottom: 40px;
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+ border-left: 3px solid #33ff99;
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+ }
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+
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+ .title-wrapper {
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+ position: relative;
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+ z-index: 2;
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+ padding: 25px 20px 30px 30px;
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+ font-family: 'Orbitron', sans-serif;
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+ }
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+
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+ .title-main {
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+ color: #e1e9f0;
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+ font-size: 2.5rem; /* Reduced font size */
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+ font-weight: 700;
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+ margin: 0;
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+ letter-spacing: 2px;
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+ display: inline-block;
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+ position: relative;
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+ text-transform: uppercase;
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+ }
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+
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+ .title-prefix {
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+ position: relative;
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+ z-index: 2;
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+ }
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+
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+ .title-subtitle {
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+ padding-left: 15px;
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+ margin-top: 5px;
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+ margin-left: 5px;
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+ }
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+
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+ .subtitle-text {
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+ color: #00c3ff;
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+ font-size: 1.2rem; /* Reduced font size */
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+ font-family: 'Orbitron', sans-serif;
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+ font-weight: 300;
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+ letter-spacing: 3px;
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+ text-transform: uppercase;
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+ display: inline-block;
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+ }
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+
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+ .glitchy-overlay {
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+ position: absolute;
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+ top: 0;
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+ left: 0;
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+ width: 100%;
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+ height: 100%;
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+ background-image: repeating-linear-gradient(0deg, rgba(0,0,0,0) 0, rgba(0,0,0,0.1) 1px, rgba(0,0,0,0) 2px);
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+ z-index: 1;
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+ }
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+
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+ /* Data box styling */
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+ .data-box {background-color: rgba(0, 0, 0, 0.2); padding: 15px; border-left: 2px solid #33ff99; margin-bottom: 20px;}
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+ .data-row {display: flex; margin-bottom: 8px;}
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+ .data-arrow {color: #33ff99; width: 20px; display: inline-block;}
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+ .data-label {color: #00c3ff; width: 80px; display: inline-block;}
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+
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+ /* Subheading styling */
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+ .subheading {color: #00c3ff; font-size: 1.1rem; margin-top: 20px; margin-bottom: 15px; font-weight: 400; border-bottom: 1px dashed rgba(0, 195, 255, 0.3); display: inline-block; text-transform: uppercase; letter-spacing: 1px; font-family: 'Orbitron', sans-serif;}
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+
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+ /* Links */
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+ a {color: #00c3ff; text-decoration: none;}
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+ a:hover {text-decoration: underline;}
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+
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+ /* Container */
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+ .container {max-width: 1200px; margin: 0 auto; padding: 40px 20px;}
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+
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+ /* Cyberpunk grid background */
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+ .cyber-grid-bg {position: fixed; top: 0; left: 0; right: 0; bottom: 0; background-color: #05071b; background-image: linear-gradient(rgba(0, 194, 255, 0.03) 1px, transparent 1px), linear-gradient(90deg, rgba(0, 194, 255, 0.03) 1px, transparent 1px); background-size: 20px 20px; z-index: -1;}
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+ </style>
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+ <html lang="en">
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+ <head>
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+ <meta charset="UTF-8">
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <title>GENETIC LEMONADE UNLEASHED v3</title>
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+ <link href="https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;600;700&family=JetBrains+Mono:wght@100;300;400;700&display=swap" rel="stylesheet">
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+ </head>
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+ <body>
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+ <div class="cyber-grid-bg"></div>
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+
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+ <div class="container">
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+ <div class="title-container">
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+ <!-- Glitchy overlay -->
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+ <div class="glitchy-overlay"></div>
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+ <!-- Main title -->
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+ <div class="title-wrapper">
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+ <h1 class="title-main">
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+ <span class="title-prefix">GENETIC</span>
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+ <span class="lemonade-text">LEMONADE</span> <!-- Static text with glow -->
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+ </h1>
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+ <div class="title-subtitle">
144
+ <span class="subtitle-text">UNLEASHED v3</span>
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+ </div>
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+ </div>
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+ </div>
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+
149
+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65b19c6c638328850e12d38c/_XKaHDAVin1ZkdlHyh09q.png)
150
+
151
+ <div class="section-container">
152
+ <div class="section-header">
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+ <div class="section-indicator"></div>
154
+ <h2 class="section-title">01 // OVERVIEW</h2>
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+ </div>
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+ <div class="section-content">
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+ <p>An experimental release.</p>
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+ <p><a href="https://huggingface.co/zerofata/L3.3-GeneticLemonade-Unleashed-70B">zerofata/GeneticLemonade-Unleashed</a> SFT+DPO QLora finetune.</p>
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+ <p>This is a creative model intended to excel at character driven RP / ERP. It has not been tested or trained on adventure stories or any large amounts of creative writing.</p>
160
+ <p>This model is designed to provide longer, narrative heavy responses where characters are portrayed accurately and proactively.</p>
161
+ </div>
162
+ </div>
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+
164
+ <div class="section-container">
165
+ <div class="section-header">
166
+ <div class="section-indicator"></div>
167
+ <h2 class="section-title">02 // SILLYTAVERN SETTINGS</h2>
168
+ </div>
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+ <div class="section-content">
170
+ <p>Play with these, they are not the 'best' settings just a stable baseline. Something interesting to note is this model supports higher temps than would normally be recommended for other L3 models.</p>
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+ <h3 class="subheading">Recommended Samplers</h3>
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+ <div class="data-box">
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+ <div class="data-row">
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+ <span class="data-arrow">></span>
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+ <span class="data-label">Temp:</span>
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+ <span>0.9 - 1.2</span>
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+ </div>
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+ <div class="data-row">
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+ <span class="data-arrow">></span>
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+ <span class="data-label">MinP:</span>
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+ <span>0.03 - 0.04</span>
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+ </div>
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+ <div class="data-row">
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+ <span class="data-arrow">></span>
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+ <span class="data-label">TopP:</span>
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+ <span>0.9 - 1.0</span>
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+ </div>
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+ <div class="data-row">
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+ <span class="data-arrow">></span>
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+ <span class="data-label">Dry:</span>
191
+ <span>0.8, 1.75, 4</span>
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+ </div>
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+ </div>
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+ <h3 class="subheading">Instruct</h3>
195
+ <div class="data-box">
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+ <p style="margin: 0;">Llama-3-Instruct-Names but you will need to uncheck "System same as user".</p>
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+ </div>
198
+ </div>
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+ </div>
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+
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+ <div class="section-container">
202
+ <div class="section-header">
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+ <div class="section-indicator"></div>
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+ <h2 class="section-title">03 // QUANTIZATIONS</h2>
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+ </div>
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+ <div class="section-content">
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+ <div style="margin-bottom: 20px;">
208
+ <h3 class="subheading">GGUF</h3>
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+ <div style="margin-left: 20px;">
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+ <span style="color: #33ff99; display: inline-block; margin-right: 10px;">> </span><a href="https://huggingface.co/mradermacher/L3.3-GeneticLemonade-Unleashed-v3-70B-i1-GGUF">iMatrix (Mradermacher)</a><br>
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+ </div>
212
+ </div>
213
+ <div>
214
+ <h3 class="subheading">EXL2</h3>
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+ <div style="margin-left: 20px;">
216
+ <span style="color: #33ff99; display: inline-block; margin-right: 10px;">> </span><a href="https://huggingface.co/zerofata/L3.3-GeneticLemonade-Unleashed-v3-70B_4bpw-hb6-exl2">4bpw</a><br>
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+ <span style="color: #33ff99; display: inline-block; margin-right: 10px;">> </span><a href="https://huggingface.co/zerofata/L3.3-GeneticLemonade-Unleashed-v3-70B_4.5bpw-hb6-exl2">4.5bpw</a><br>
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+ <span style="color: #33ff99; display: inline-block; margin-right: 10px;">> </span><a href="https://huggingface.co/zerofata/L3.3-GeneticLemonade-Unleashed-v3-70B_6bpw-hb8-exl2">6bpw</a>
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+ </div>
220
+ </div>
221
+ </div>
222
+ </div>
223
+
224
+ <div class="section-container">
225
+ <div class="section-header">
226
+ <div class="section-indicator"></div>
227
+ <h2 class="section-title">04 // TRAINING PROCESS</h2>
228
+ </div>
229
+ <div class="section-content">
230
+ <p>The model first went through SFT with a small synthetic dataset of 2.9 million tokens, approximately 750 conversations. Primarily RP data with small amounts of random instruct / assistant data and creative writing.</p>
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+ <p>The model then went through DPO training using approx 1100 chosen examples from the SFT dataset that were of exceptional quality or showed verifiable instruction following. Rejected samples were generated using another Llama 3.3 finetune that is known for poor instruction following.</p>
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+ </div>
233
+ </div>
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+ </div>
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+ <h3 class="subheading">Axolotl configs</h3>
236
+ <p>Neither are optimized for cost / performance efficiency, YMMV.</p>
237
+ <h3>SFT 1*H200</h3>
238
+
239
+ ```yml
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+ # ====================
241
+ # MODEL CONFIGURATION
242
+ # ====================
243
+ base_model: zerofata/L3.3-GeneticLemonade-Unleashed-70B
244
+ model_type: AutoModelForCausalLM
245
+ tokenizer_type: AutoTokenizer
246
+ special_tokens:
247
+ pad_token: "<|finetune_right_pad_id|>"
248
+ chat_template: llama3
249
+
250
+ # ====================
251
+ # DATASET CONFIGURATION
252
+ # ====================
253
+ datasets:
254
+ - path: ./dataset.jsonl
255
+ type: chat_template
256
+ split: train
257
+ chat_template_strategy: tokenizer
258
+ field_messages: messages
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+ message_property_mappings:
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+ role: role
261
+ content: content
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+ roles:
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+ user: ["user"]
264
+ assistant: ["assistant"]
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+ system: ["system"]
266
+
267
+ test_datasets:
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+ - path: ./validate_dataset.jsonl
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+ type: chat_template
270
+ split: train
271
+ chat_template_strategy: tokenizer
272
+ field_messages: messages
273
+ message_property_mappings:
274
+ role: role
275
+ content: content
276
+ roles:
277
+ user: ["user"]
278
+ assistant: ["assistant"]
279
+ system: ["system"]
280
+
281
+ dataset_prepared_path:
282
+ train_on_inputs: false # Only train on assistant responses
283
+
284
+ # ====================
285
+ # QLORA CONFIGURATION
286
+ # ====================
287
+ adapter: qlora
288
+ load_in_4bit: true
289
+ lora_r: 64
290
+ lora_alpha: 128
291
+ lora_dropout: 0.1
292
+ lora_target_linear: true
293
+ # lora_modules_to_save: # Uncomment only if you added NEW tokens
294
+
295
+ # ====================
296
+ # TRAINING PARAMETERS
297
+ # ====================
298
+ num_epochs: 2
299
+ micro_batch_size: 4
300
+ gradient_accumulation_steps: 2
301
+ learning_rate: 1.5e-5
302
+ optimizer: paged_adamw_8bit
303
+ lr_scheduler: rex
304
+ warmup_ratio: 0.05
305
+ weight_decay: 0.01
306
+ max_grad_norm: 1.0
307
+
308
+ # ====================
309
+ # SEQUENCE & PACKING
310
+ # ====================
311
+ sequence_len: 8192
312
+ sample_packing: true
313
+ eval_sample_packing: false
314
+ pad_to_sequence_len: true
315
+
316
+ # ====================
317
+ # HARDWARE OPTIMIZATIONS
318
+ # ====================
319
+ bf16: auto
320
+ flash_attention: true
321
+ gradient_checkpointing: true
322
+
323
+ # ====================
324
+ # EVALUATION & CHECKPOINTING
325
+ # ====================
326
+ evaluation_strategy: steps
327
+ eval_steps: 5
328
+ save_strategy: steps
329
+ save_steps: 5
330
+ save_total_limit: 5 # Keep best + last few checkpoints
331
+ load_best_model_at_end: true
332
+ metric_for_best_model: eval_loss
333
+ greater_is_better: false
334
+ early_stopping_patience: 5
335
+
336
+ # ====================
337
+ # LOGGING & OUTPUT
338
+ # ====================
339
+ output_dir: ./output_model
340
+ logging_steps: 2
341
+ save_safetensors: true
342
+
343
+ # ====================
344
+ # WANDB TRACKING
345
+ # ====================
346
+ wandb_project: project_name
347
+ # wandb_entity: your_entity
348
+ # wandb_name: your_run_name
349
+
350
+ ```
351
+ <h3>DPO 2*H200</h3>
352
+
353
+ ```yml
354
+ # ====================
355
+ # MODEL CONFIGURATION
356
+ # ====================
357
+ base_model: ApocalypseParty/unleashed-fulldata30
358
+ model_type: AutoModelForCausalLM
359
+ tokenizer_type: AutoTokenizer
360
+ special_tokens: {}
361
+ chat_template: tokenizer_default
362
+
363
+ # ====================
364
+ # RL/DPO CONFIGURATION
365
+ # ====================
366
+ rl: dpo
367
+ rl_beta: 0.07
368
+
369
+ # ====================
370
+ # DATASET CONFIGURATION
371
+ # ====================
372
+ datasets:
373
+ - path: ./dpo_cleaned-v3_deduplicated.jsonl
374
+ type: chat_template.default
375
+ field_messages: conversation
376
+ field_chosen: chosen
377
+ field_rejected: rejected
378
+ message_property_mappings:
379
+ role: role
380
+ content: content
381
+ roles:
382
+ system: ["system"]
383
+ user: ["user"]
384
+ assistant: ["assistant"]
385
+ dataset_prepared_path:
386
+ train_on_inputs: false # Only train on assistant responses
387
+
388
+ # ====================
389
+ # QLORA CONFIGURATION
390
+ # ====================
391
+ adapter: qlora
392
+ load_in_4bit: true
393
+ lora_r: 32
394
+ lora_alpha: 64
395
+ lora_dropout: 0.05
396
+ lora_target_linear: true
397
+ # lora_modules_to_save: # Uncomment only if you added NEW tokens
398
+
399
+ # ====================
400
+ # TRAINING PARAMETERS
401
+ # ====================
402
+ num_epochs: 1
403
+ micro_batch_size: 4
404
+ gradient_accumulation_steps: 2
405
+ learning_rate: 2e-6
406
+ optimizer: adamw_8bit
407
+ lr_scheduler: cosine
408
+ warmup_steps: 5
409
+ weight_decay: 0.01
410
+ max_grad_norm: 1.0
411
+
412
+ # ====================
413
+ # SEQUENCE CONFIGURATION
414
+ # ====================
415
+ sequence_len: 4096
416
+ pad_to_sequence_len: true
417
+
418
+ # ====================
419
+ # HARDWARE OPTIMIZATIONS
420
+ # ====================
421
+ bf16: auto
422
+ tf32: false
423
+ flash_attention: true
424
+ gradient_checkpointing: offload
425
+ deepspeed: deepspeed_configs/zero1.json
426
+
427
+ # ====================
428
+ # CHECKPOINTING
429
+ # ====================
430
+ save_steps: 10
431
+ save_total_limit: 10
432
+ load_best_model_at_end: true
433
+ metric_for_best_model: eval_loss
434
+ greater_is_better: false
435
+
436
+ # ====================
437
+ # LOGGING & OUTPUT
438
+ # ====================
439
+ output_dir: ./dpo_model
440
+ logging_steps: 2
441
+ save_safetensors: true
442
+
443
+ # ====================
444
+ # WANDB TRACKING
445
+ # ====================
446
+ wandb_project: project_name
447
+ # wandb_entity: your_entity
448
+ # wandb_name: your_run_name
449
+ ```
450
+ </body>
451
+ </html>
config.json ADDED
@@ -0,0 +1,46 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architectures": [
3
+ "LlamaForCausalLM"
4
+ ],
5
+ "attention_bias": false,
6
+ "attention_dropout": 0.0,
7
+ "bos_token_id": 128000,
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+ "bos_token": "<|begin_of_text|>",
2053
+ "chat_template": "{{- bos_token }}\n{%- if custom_tools is defined %}\n {%- set tools = custom_tools %}\n{%- endif %}\n{%- if not tools_in_user_message is defined %}\n {%- set tools_in_user_message = true %}\n{%- endif %}\n{%- if not date_string is defined %}\n {%- set date_string = \"26 Jul 2024\" %}\n{%- endif %}\n{%- if not tools is defined %}\n {%- set tools = none %}\n{%- endif %}\n\n{#- This block extracts the system message, so we can slot it into the right place. #}\n{%- if messages[0]['role'] == 'system' %}\n {%- set system_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n{%- else %}\n {%- set system_message = \"\" %}\n{%- endif %}\n\n{#- System message + builtin tools #}\n{{- \"<|start_header_id|>system<|end_header_id|>\\n\\n\" }}\n{%- if builtin_tools is defined or tools is not none %}\n {{- \"Environment: ipython\\n\" }}\n{%- endif %}\n{%- if builtin_tools is defined %}\n {{- \"Tools: \" + builtin_tools | reject('equalto', 'code_interpreter') | join(\", \") + \"\\n\\n\"}}\n{%- endif %}\n{{- \"Cutting Knowledge Date: December 2023\\n\" }}\n{{- \"Today Date: \" + date_string + \"\\n\\n\" }}\n{%- if tools is not none and not tools_in_user_message %}\n {{- \"You have access to the following functions. To call a function, please respond with JSON for a function call.\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n{%- endif %}\n{{- system_message }}\n{{- \"<|eot_id|>\" }}\n\n{#- Custom tools are passed in a user message with some extra guidance #}\n{%- if tools_in_user_message and not tools is none %}\n {#- Extract the first user message so we can plug it in here #}\n {%- if messages | length != 0 %}\n {%- set first_user_message = messages[0]['content']|trim %}\n {%- set messages = messages[1:] %}\n {%- else %}\n {{- raise_exception(\"Cannot put tools in the first user message when there's no first user message!\") }}\n{%- endif %}\n {{- '<|start_header_id|>user<|end_header_id|>\\n\\n' -}}\n {{- \"Given the following functions, please respond with a JSON for a function call \" }}\n {{- \"with its proper arguments that best answers the given prompt.\\n\\n\" }}\n {{- 'Respond in the format {\"name\": function name, \"parameters\": dictionary of argument name and its value}.' }}\n {{- \"Do not use variables.\\n\\n\" }}\n {%- for t in tools %}\n {{- t | tojson(indent=4) }}\n {{- \"\\n\\n\" }}\n {%- endfor %}\n {{- first_user_message + \"<|eot_id|>\"}}\n{%- endif %}\n\n{%- for message in messages %}\n {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}\n {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\\n\\n'+ message['content'] | trim + '<|eot_id|>' }}\n {%- elif 'tool_calls' in message %}\n {%- if not message.tool_calls|length == 1 %}\n {{- raise_exception(\"This model only supports single tool-calls at once!\") }}\n {%- endif %}\n {%- set tool_call = message.tool_calls[0].function %}\n {%- if builtin_tools is defined and tool_call.name in builtin_tools %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- \"<|python_tag|>\" + tool_call.name + \".call(\" }}\n {%- for arg_name, arg_val in tool_call.arguments | items %}\n {{- arg_name + '=\"' + arg_val + '\"' }}\n {%- if not loop.last %}\n {{- \", \" }}\n {%- endif %}\n {%- endfor %}\n {{- \")\" }}\n {%- else %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' -}}\n {{- '{\"name\": \"' + tool_call.name + '\", ' }}\n {{- '\"parameters\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- \"}\" }}\n {%- endif %}\n {%- if builtin_tools is defined %}\n {#- This means we're in ipython mode #}\n {{- \"<|eom_id|>\" }}\n {%- else %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n {%- elif message.role == \"tool\" or message.role == \"ipython\" %}\n {{- \"<|start_header_id|>ipython<|end_header_id|>\\n\\n\" }}\n {%- if message.content is mapping or message.content is iterable %}\n {{- message.content | tojson }}\n {%- else %}\n {{- message.content }}\n {%- endif %}\n {{- \"<|eot_id|>\" }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|start_header_id|>assistant<|end_header_id|>\\n\\n' }}\n{%- endif %}\n",
2054
+ "clean_up_tokenization_spaces": true,
2055
+ "eos_token": "<|eot_id|>",
2056
+ "extra_special_tokens": {},
2057
+ "model_input_names": [
2058
+ "input_ids",
2059
+ "attention_mask"
2060
+ ],
2061
+ "model_max_length": 131072,
2062
+ "pad_token": "<|finetune_right_pad_id|>",
2063
+ "tokenizer_class": "PreTrainedTokenizer"
2064
+ }