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@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+Q9BKYVW476PWX2JN7PG83YWEF0.jpeg filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,501 @@
+---
+license: llama3.3
+base_model: meta-llama/Llama-3.3-70B-Instruct
+tags:
+- llama-3.3
+- finetune
+- roleplay
+- chat
+- wings-of-fire
+- nsfw
+- not-for-all-audiences
+---
+
+<style>
+body {
+  font-family: 'Quicksand', sans-serif;
+  /* Replaced purple gradient with a warm, fiery one */
+  background: linear-gradient(135deg, #4a1e00 0%, #1c0a00 100%);
+  /* Changed text color to a warmer, parchment-like off-white */
+  color: #F5EFE6;
+  margin: 0;
+  padding: 0;
+  font-size: 16px;
+}
+
+h1, h2, h3, h4, summary {
+    font-family: 'Cinzel', serif;
+}
+
+.container {
+  margin: 20px auto;
+  max-width: 900px;
+  background-color: rgba(28, 22, 18, 0.95);
+  padding: 30px;
+  border-radius: 12px;
+  box-shadow: 0 4px 20px rgba(255, 140, 0, 0.15);
+  border: 1px solid rgba(255, 140, 0, 0.2);
+  outline: 1px solid rgba(255, 140, 0, 0.5);
+  outline-offset: -1px;
+  position: relative;
+}
+
+.container::before {
+  content: '';
+  position: absolute;
+  top: -1px;
+  left: -1px;
+  right: -1px;
+  bottom: -1px;
+  border: 1px solid rgba(255, 165, 0, 0.98);
+  border-radius: 12px;
+  pointer-events: none;
+  animation: borderGlow 2.5s ease-in-out infinite;
+}
+
+@keyframes borderGlow {
+  0% {
+    box-shadow: 0 0 5px rgba(255, 165, 0, 0.98);
+  }
+  50% {
+    box-shadow: 0 0 12px rgba(255, 165, 0, 0.98);
+  }
+  100% {
+    box-shadow: 0 0 5px rgba(255, 165, 0, 0.98);
+  }
+}
+
+.header h1 {
+  font-size: 32px;
+  color: #FFA500;
+  margin: 0 0 20px 0;
+  text-align: center;
+  text-shadow: 0 0 12px rgba(255, 100, 0, 0.6);
+}
+
+.info img {
+  width: 100%;
+  max-width: 700px;
+  display: block;
+  margin: 0 auto 25px auto;
+  border-radius: 10px;
+  box-shadow: 0 0 20px rgba(255, 140, 0, 0.25);
+  border: 1px solid rgba(255, 140, 0, 0.2);
+  outline: 1px solid rgba(255, 140, 0, 0.5);
+  outline-offset: -1px;
+}
+
+a {
+  color: #FFD700;
+  text-decoration: none;
+  transition: color 0.3s ease;
+}
+
+a:hover {
+  color: #FFDAB9;
+}
+
+.button {
+  display: inline-block;
+  background-color: #E55B00;
+  color: #FFFFFF;
+  padding: 12px 24px;
+  border-radius: 5px;
+  cursor: pointer;
+  text-decoration: none;
+  font-family: 'Cinzel', serif;
+  font-weight: 600;
+  transition: all 0.3s ease;
+  border: 1px solid transparent;
+}
+
+.button:hover {
+  background-color: #FF8C00;
+  box-shadow: 0 0 15px rgba(255, 140, 0, 0.5);
+  transform: translateY(-2px);
+}
+
+pre {
+  background-color: rgba(45, 35, 25, 0.95);
+  padding: 15px;
+  border-radius: 5px;
+  overflow-x: auto;
+  border: 1px solid rgba(255, 140, 0, 0.2);
+  outline: 1px solid rgba(255, 140, 0, 0.5);
+  outline-offset: -1px;
+}
+
+code {
+  font-family: 'Courier New', monospace;
+  /* Code text uses the new base text color */
+  color: #F5EFE6;
+}
+
+/* Section Container */
+.section-container {
+  margin: 40px 0;
+}
+
+h2 {
+    font-size: 26px;
+    /* Section headers are orange */
+    color: #FFA500;
+    text-shadow: 0 0 10px rgba(255, 140, 0, 0.5);
+    border-bottom: 1px solid rgba(255, 140, 0, 0.2);
+    padding-bottom: 10px;
+    margin-bottom: 20px;
+}
+
+.info-card {
+  /* Card background is a warm dark brown */
+  background: rgba(45, 35, 25, 0.95);
+  border: 1px solid rgba(255, 140, 0, 0.2);
+  border-radius: 8px;
+  overflow: hidden;
+  margin-bottom: 25px;
+}
+
+.info-header {
+  /* Header background has an orange tint */
+  background: rgba(255, 140, 0, 0.1);
+  padding: 20px;
+  border-bottom: 1px solid rgba(255, 140, 0, 0.2);
+}
+
+.info-header h3 {
+  /* Card titles are orange */
+  color: #FFA500;
+  margin: 0 0 10px 0;
+  font-size: 22px;
+  text-shadow: 0 0 5px rgba(255, 140, 0, 0.3);
+}
+
+.model-tags {
+  display: flex;
+  gap: 8px;
+  flex-wrap: wrap;
+}
+
+.model-tag {
+  /* Tags are now gold-themed */
+  background: rgba(218, 165, 32, 0.15);
+  color: #FFD700;
+  padding: 4px 8px;
+  border-radius: 4px;
+  font-size: 12px;
+  border: 1px solid rgba(218, 165, 32, 0.3);
+  font-family: 'Quicksand', sans-serif;
+}
+
+.card-content {
+  padding: 20px;
+  line-height: 1.7;
+}
+
+.card-content p, .card-content li {
+    margin-bottom: 1em;
+}
+
+.card-content p:last-child, .card-content li:last-child {
+    margin-bottom: 0;
+}
+
+.card-content ul {
+    list-style: none;
+    padding-left: 20px;
+}
+
+.card-content li::before {
+    content: '✦';
+    /* Bullet points are gold */
+    color: #FFD700;
+    font-weight: bold;
+    display: inline-block;
+    width: 1em;
+    margin-left: -1.2em;
+    font-size: 1.2em;
+    line-height: 1;
+}
+
+.card-content strong {
+    /* Strong text is gold */
+    color: #FFD700;
+    font-weight: 600;
+}
+
+/* Configuration */
+.config-container {
+  background: rgba(45, 35, 25, 0.95);
+  border: 1px solid rgba(255, 140, 0, 0.2);
+  border-radius: 8px;
+  overflow: hidden;
+}
+
+.config-header {
+  background: rgba(255, 140, 0, 0.1);
+  padding: 15px 20px;
+  border-bottom: 1px solid rgba(255, 140, 0, 0.2);
+}
+
+.config-header h3 {
+    margin: 0;
+    color: #FFA500;
+    font-size: 22px;
+}
+
+.config-content {
+  padding: 20px;
+  display: grid;
+  grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+  gap: 20px;
+}
+
+.config-item {
+  display: flex;
+  flex-direction: column;
+  gap: 5px;
+}
+
+.config-label {
+  /* Config labels are gold */
+  color: #FFD700;
+  font-size: 14px;
+  font-weight: 500;
+  font-family: 'Quicksand', sans-serif;
+}
+
+.config-value {
+  /* Config values use the new base text color */
+  color: #F5EFE6;
+  font-family: 'Courier New', monospace;
+  font-size: 18px;
+  font-weight: bold;
+}
+
+/* Link arrow animation */
+.link-arrow {
+  display: inline-block;
+  transition: transform 0.3s ease;
+}
+
+a:hover .link-arrow {
+  transform: translateX(3px);
+}
+
+.support-section {
+    text-align: center;
+    margin-top: 40px;
+    background: rgba(45, 35, 25, 0.95);
+    border: 1px solid rgba(255, 140, 0, 0.2);
+    border-radius: 8px;
+    padding: 20px;
+}
+
+.support-section p {
+    margin-bottom: 15px;
+    font-size: 1.1em;
+    margin-top: 0;
+}
+
+summary {
+    cursor: pointer;
+    list-style: none; /* Remove default arrow */
+    outline: none;
+    display: flex;
+    align-items: flex-start; /* Align items to the top to respect h2's vertical space */
+}
+summary::-webkit-details-marker {
+    display: none;
+}
+summary::before {
+    content: '▶';
+    font-size: 1.2em;
+    color: #FFA500; /* Match h2 color */
+    margin-right: 15px;
+    padding-top: 5px; /* Adjust vertical alignment with h2 text */
+    transition: transform 0.2s ease;
+    flex-shrink: 0; /* Prevent the arrow from shrinking */
+}
+details[open] > summary::before {
+    transform: rotate(90deg);
+}
+summary > h2 {
+    flex-grow: 1;
+}
+</style>
+<div class="container">
+<link href="https://fonts.googleapis.com/css2?family=Cinzel:wght@400;500;600&family=Quicksand:wght@400;500&display=swap" rel="stylesheet">
+<div class="header">
+  <h1>L3.3-70B-Animus-V12</h1>
+</div>
+<div class="info">
+  <img src="Q9BKYVW476PWX2JN7PG83YWEF0.jpeg" alt="Wings_of_Fire" width="700">
+
+  <div class="support-section">
+    <p><strong>Send me your support to help me feed the data beast! also taking comissions for universe specific models</strong></p>
+    <a href="https://ko-fi.com/som1tokmynam" target="_blank" class="button">
+      Support on Ko-fi
+    </a>
+  </div>
+
+<div class="section-container">
+  <details>
+    <summary><h2>Quantized Models</h2></summary>
+    <div class="info-card">
+      <div class="card-content">
+        <p>The quantized model files are available for download. Click the buttons below to view the files.</p>
+        <a href="https://huggingface.co/Darkhn/L3.3-70B-Animus-V12.0-GGUF" target="_blank" class="button">
+          Download GGUF Files <span class="link-arrow">→</span>
+        </a>
+        <a href="https://huggingface.co/Darkhn/L3.3-70B-Animus-V12.0-EXl2" target="_blank" class="button">
+          Download EXL2 Files <span class="link-arrow">→</span>
+        </a>
+        <a href="https://huggingface.co/ReadyArt/Darkhn_L3.3-Animus-V12.0-EXL3" target="_blank" class="button">
+          Download EXL3 Files (coming soon) <span class="link-arrow">→</span>
+        </a>
+      </div>
+    </div>
+  </details>
+</div>
+
+  <div class="section-container">
+    <details>
+      <summary><h2>Character Card & Lore Book</h2></summary>
+      <div class="info-card">
+        <div class="card-content">
+          <p>For the best roleplaying experience, it is highly recommended to use the provided character card and lore book. These files help guide the model's persona and provide rich, in-universe context.</p>
+          <a href="https://huggingface.co/Darkhn/Sampler_settings_and_system_prompt/tree/main/character_card" target="_blank" class="button">
+            Download Files <span class="link-arrow">→</span>
+          </a>
+        </div>
+      </div>
+    </details>
+  </div>
+
+  <div class="section-container">
+    <details>
+      <summary><h2>Sampler Presets</h2></summary>
+      <div class="info-card">
+        <div class="card-content">
+          <p>For a seamless setup in SillyTavern, you can download pre-configured sampler presets. These are tuned to provide an optimal balance between creativity and narrative coherence for this model.</p>
+          <p>Simply download the <code>.json</code> file below and import it into SillyTavern's sampler presets menu.</p>
+          <a href="https://huggingface.co/Darkhn/Sampler_settings_and_system_prompt/tree/main" target="_blank" class="button">
+            Download SillyTavern Presets <span class="link-arrow">→</span>
+          </a>
+          <p><li>For those that dont use silly tavern, Samplers settings are:</li></p>
+          <ul>
+              <p><strong>Temp:</strong> 0.8-1.2</p>
+              <p><strong>Min P:</strong> 0.02</p>
+              <p><strong>Dry:</strong> 0.8 , 1.75, 4</p>
+          <p><li>Creative Alternative if supported:</li></p>
+              <p><strong>Temp:</strong> 1</p>
+              <p><strong>Min P:</strong> 0.03</p>
+              <p><strong>Nsigma:</strong> 2</p>
+              <p><strong>Dry:</strong> 0.8 , 1.75, 4</p>
+          </ul>
+        </div>
+      </div>
+    </details>
+  </div>
+
+  <div class="section-container">
+    <details open>
+      <summary><h2>Model Description</h2></summary>
+      <div class="info-card">
+        <div class="card-content">
+          <p>This is <strong>Version 12</strong>, a significant advancement in the Animus series built on a completely new training philosophy. Instead of merging previous models, V12 is a direct fine-tune of <strong>Llama 3.3 70B Instruct</strong>. This focused approach has resulted in what is being called the most coherent and lore-adherent version to date.</p>
+          <p>V12's strength comes from a novel dataset designed to teach the model the <em>why</em> behind the lore, not just the <em>what</em>. The training data is a mix of:</p>
+            <ul>
+                <li><strong>A 3,000-example Q&A dataset:</strong> This data is framed as an in-character study session, like a student at Jade Mountain Academy learning about the history, relationships, and politics of Pyrrhia's tribes. This provides a deep, contextual understanding of the universe.</li>
+                <li><strong>A 3,000-example uncensored roleplay dataset:</strong> The same high-quality, mature roleplay scenarios used in previous versions, ensuring the model maintains its engaging and dynamic narrative capabilities.</li>
+            </ul>
+          <p>The result is a model with <strong>exceptionally strong prose and a deep grasp of in-universe lore</strong>, making for a highly immersive and accurate roleplaying experience.</p>
+        </div>
+      </div>
+    </details>
+  </div>
+  
+  <div class="section-container">
+    <details open>
+      <summary><h2>Training Details</h2></summary>
+      <div class="info-card">
+          <div class="info-header">
+              <h3>V12 Training Process</h3>
+          </div>
+          <div class="card-content">
+              <p>V12 marks a shift from model merging to a focused, direct fine-tuning approach. This allows for greater control over the final model's characteristics.</p>
+              <ul>
+                  <li><strong>Base Model:</strong> Llama 3.3 70B Instruct</li>
+                  <li><strong>Hardware:</strong> 1x NVIDIA B200</li>
+                  <li><strong>Training Time:</strong> 22 hours</li>
+                  <li><strong>Epochs:</strong> 4</li>
+                  <li><strong>LoRA Rank:</strong> 256</li>
+                  <li><strong>Scheduler:</strong> Cosine (a change from the `rex` scheduler used for V11)</li>
+              </ul>
+          </div>
+      </div>
+      <div class="info-card">
+        <div class="info-header">
+            <h3>Feature Update: Removal of DM Choices</h3>
+        </div>
+        <div class="card-content">
+            <p>A key feature in previous test versions—the presentation of multiple-choice actions (e.g., A, B, C) to guide the user—has been <strong>removed</strong>.</p>
+            <p>While a promising concept, this feature needs further refinement to ensure it enhances, rather than restricts, the roleplaying experience. It may be reintroduced in a more polished form in a future release. For now, the model returns to a more traditional, open-ended prose format.</p>
+        </div>
+    </div>
+      <div class="info-card">
+          <div class="info-header">
+              <h3>Training Dataset</h3>
+          </div>
+          <div class="card-content">
+              <p>The V12 dataset consists of <strong>6,000 high-quality examples</strong>, a combination of two distinct types:</p>
+              <ul>
+                  <li><strong>In-Character Q&A (3,000 examples):</strong> This new dataset simulates a student at Jade Mountain Academy studying the world's lore. It's composed of roleplay-style questions and answers covering tribe history, family dynamics, and political relationships. This method builds a foundational, interconnected understanding of the lore.</li>
+                  <li><strong>Uncensored Roleplay (3,000 examples):</strong> This is the same mature, canon-centric dataset refined for previous versions. It explores pivotal "what-if" scenarios from the books using only canon characters, ensuring the model can handle complex and dramatic narratives.</li>
+              </ul>
+              <p>Both datasets underwent a rigorous cleaning process to remove formatting artifacts, such as <code>**scene transitions**</code>, resulting in a cleaner and more natural narrative style.</p>
+          </div>
+      </div>
+    </details>
+  </div>
+  
+  <div class="section-container">
+    <details>
+      <summary><h2>Intended Use & Limitations</h2></summary>
+      <div class="info-card">
+          <div class="card-content">
+              <ul>
+                  <li><strong>Intended Use:</strong> The primary purpose of this model is for creative and roleplaying within the <em>Wings of Fire</em> universe. However, user feedback indicates it is also highly effective for general-purpose roleplaying.</li>
+                  <li><strong>Limitations & Quirks:</strong>
+                      <ul>
+                          <li>Performance on tasks outside of its training domain (general knowledge, coding, etc.) is not guaranteed and will likely be poor.</li>
+                          <li><strong>Versatility:</strong> While it appears to be only a <em>Wings of Fire</em> tuned model, users have reported it is very capable of performing normal roleplay with other settings and characters.</li>
+                          <li>The model may "hallucinate" or generate plausible but non-canonical information, especially when pushed outside the established "what-if" scenarios.</li>
+                          <li><strong>Content:</strong> The training data includes mature and darker themes from the <em>Wings of Fire</em> series, such as conflict, character death, and moral ambiguity. The model is capable of generating content reflecting these themes. As always, it is up to the user what they do with it.</li>
+                          <li><strong>Formatting:</strong> Training data was cleaned to remove narrative artifacts like <code>**scene transitions**</code>. The model should now produce cleaner prose.</li>
+                          <li><strong>Safety:</strong> This model has not undergone additional safety alignment beyond what was included in its base Llama 3.3 model. Standard responsible AI practices should be followed.</li>
+                      </ul>
+                  </li>
+              </ul>
+          </div>
+      </div>
+    </details>
+  </div>
+
+  <div class="section-container">
+    <details>
+      <summary><h2>Acknowledgements</h2></summary>
+      <div class="info-card">
+          <div class="card-content">
+              <ul>
+                  <li>Credit to Meta for the powerful Llama 3.3 architecture.</li>
+                  <li>Credit to Google for the Gemini Pro model, used in dataset generation.</li>
+                  <li>Credit to those who donated to my KoFi to make this run Possible Mainly @sunnybeyond & @phaelon</li>
+              </ul>
+          </div>
+      </div>
+    </details>
+  </div>
+
+</div>
+</div>

chat_template.jinja

@@ -0,0 +1,109 @@
+{{- bos_token }}
+{%- if custom_tools is defined %}
+    {%- set tools = custom_tools %}
+{%- endif %}
+{%- if not tools_in_user_message is defined %}
+    {%- set tools_in_user_message = true %}
+{%- endif %}
+{%- if not date_string is defined %}
+    {%- set date_string = "26 Jul 2024" %}
+{%- endif %}
+{%- if not tools is defined %}
+    {%- set tools = none %}
+{%- endif %}
+
+{#- This block extracts the system message, so we can slot it into the right place. #}
+{%- if messages[0]['role'] == 'system' %}
+    {%- set system_message = messages[0]['content']|trim %}
+    {%- set messages = messages[1:] %}
+{%- else %}
+    {%- set system_message = "" %}
+{%- endif %}
+
+{#- System message + builtin tools #}
+{{- "<|start_header_id|>system<|end_header_id|>\n\n" }}
+{%- if builtin_tools is defined or tools is not none %}
+    {{- "Environment: ipython\n" }}
+{%- endif %}
+{%- if builtin_tools is defined %}
+    {{- "Tools: " + builtin_tools | reject('equalto', 'code_interpreter') | join(", ") + "\n\n"}}
+{%- endif %}
+{{- "Cutting Knowledge Date: December 2023\n" }}
+{{- "Today Date: " + date_string + "\n\n" }}
+{%- if tools is not none and not tools_in_user_message %}
+    {{- "You have access to the following functions. To call a function, please respond with JSON for a function call." }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+{%- endif %}
+{{- system_message }}
+{{- "<|eot_id|>" }}
+
+{#- Custom tools are passed in a user message with some extra guidance #}
+{%- if tools_in_user_message and not tools is none %}
+    {#- Extract the first user message so we can plug it in here #}
+    {%- if messages | length != 0 %}
+        {%- set first_user_message = messages[0]['content']|trim %}
+        {%- set messages = messages[1:] %}
+    {%- else %}
+        {{- raise_exception("Cannot put tools in the first user message when there's no first user message!") }}
+{%- endif %}
+    {{- '<|start_header_id|>user<|end_header_id|>\n\n' -}}
+    {{- "Given the following functions, please respond with a JSON for a function call " }}
+    {{- "with its proper arguments that best answers the given prompt.\n\n" }}
+    {{- 'Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}.' }}
+    {{- "Do not use variables.\n\n" }}
+    {%- for t in tools %}
+        {{- t | tojson(indent=4) }}
+        {{- "\n\n" }}
+    {%- endfor %}
+    {{- first_user_message + "<|eot_id|>"}}
+{%- endif %}
+
+{%- for message in messages %}
+    {%- if not (message.role == 'ipython' or message.role == 'tool' or 'tool_calls' in message) %}
+        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' }}
+    {%- elif 'tool_calls' in message %}
+        {%- if not message.tool_calls|length == 1 %}
+            {{- raise_exception("This model only supports single tool-calls at once!") }}
+        {%- endif %}
+        {%- set tool_call = message.tool_calls[0].function %}
+        {%- if builtin_tools is defined and tool_call.name in builtin_tools %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- "<|python_tag|>" + tool_call.name + ".call(" }}
+            {%- for arg_name, arg_val in tool_call.arguments | items %}
+                {{- arg_name + '="' + arg_val + '"' }}
+                {%- if not loop.last %}
+                    {{- ", " }}
+                {%- endif %}
+                {%- endfor %}
+            {{- ")" }}
+        {%- else  %}
+            {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' -}}
+            {{- '{"name": "' + tool_call.name + '", ' }}
+            {{- '"parameters": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- "}" }}
+        {%- endif %}
+        {%- if builtin_tools is defined %}
+            {#- This means we're in ipython mode #}
+            {{- "<|eom_id|>" }}
+        {%- else %}
+            {{- "<|eot_id|>" }}
+        {%- endif %}
+    {%- elif message.role == "tool" or message.role == "ipython" %}
+        {{- "<|start_header_id|>ipython<|end_header_id|>\n\n" }}
+        {%- if message.content is mapping or message.content is iterable %}
+            {{- message.content | tojson }}
+        {%- else %}
+            {{- message.content }}
+        {%- endif %}
+        {{- "<|eot_id|>" }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}

config.json

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+{
+    "architectures": [
+        "LlamaForCausalLM"
+    ],
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 128000,
+    "eos_token_id": [
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+    "hidden_act": "silu",
+    "hidden_size": 8192,
+    "initializer_range": 0.02,
+    "intermediate_size": 28672,
+    "max_position_embeddings": 131072,
+    "mlp_bias": false,
+    "model_type": "llama",
+    "num_attention_heads": 64,
+    "num_hidden_layers": 80,
+    "num_key_value_heads": 8,
+    "pretraining_tp": 1,
+    "rms_norm_eps": 1e-05,
+    "rope_scaling": {
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+        "high_freq_factor": 4.0,
+        "low_freq_factor": 1.0,
+        "original_max_position_embeddings": 8192,
+        "rope_type": "llama3"
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+    "rope_theta": 500000.0,
+    "tie_word_embeddings": false,
+    "torch_dtype": "bfloat16",
+    "transformers_version": "4.53.1",
+    "use_cache": true,
+    "vocab_size": 128256,
+    "quantization_config": {
+        "quant_method": "exl3",
+        "version": "0.0.6",
+        "bits": 3.0,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "cols": 2048
+        },
+        "out_scales": "auto"
+    }
+}

generation_config.json

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+{
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+  "do_sample": true,
+  "eos_token_id": [
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+    128008,
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+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.53.1"
+}

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special_tokens_map.json

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+  },
+  "bos_token": "<|begin_of_text|>",
+  "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",
+  "clean_up_tokenization_spaces": true,
+  "eos_token": "<|eot_id|>",
+  "extra_special_tokens": {},
+  "model_input_names": [
+    "input_ids",
+    "attention_mask"
+  ],
+  "model_max_length": 131072,
+  "pad_token": "<|finetune_right_pad_id|>",
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}