Maestro-10B / README.md
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---
language:
- en
base_model:
- arcee-ai/Virtuoso-Lite
datasets:
- Open-Orca/OpenOrca
pipeline_tag: text-generation
library_name: transformers
tags:
- unsloth
- trl
- sft
---
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</style>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Maestro-10B</title>
<link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
<link href="styles.css" rel="stylesheet">
</head>
<body>
<div class="container">
<div class="header">
<h1>Maestro-10B</h1>
</div>
<div class="info">
<img src="Maestro-Logo.png" alt="Model banner">
<div class="creator-section">
<div class="creator-badge">
<span class="creator-label">Created by</span>
<a href="https://huggingface.co/suayptalha" target="_blank" class="creator-link">
<span class="creator-name">suayptalha</span>
<span class="creator-arrow">→</span>
</a>
</div>
</div>
<div class="model-info">
<h2>Model Information</h2>
<div class="info-card">
<div class="info-header">
<h3>Maestro-10B</h3>
<div class="model-tags">
<span class="model-tag">suayptalha/Maestro-10B</span>
<span class="model-tag">arcee-ai/Virtuoso-Lite</span>
<span class="model-tag">DeepSeek-V3</span>
<span class="model-tag">10b Parameters</span>
</div>
</div>
<div class="model-composition">
<h4>Base Model</h4>
<ul class="composition-list">
<li><span class="model-component"><a href="arcee-ai/Virtuoso-Lite" target="_blank">Virtuoso-Lite</a></span></li>
</ul>
</div>
<div class="model-description">
Maestro-10B is a 10 billion parameter model fine-tuned from Virtuoso-Lite,
a next-generation language model developed by arcee-ai. Virtuoso-Lite itself
is based on the Llama-3 architecture, distilled from Deepseek-v3 using
approximately 1.1 billion tokens/logits. This distillation process allows
Virtuoso-Lite to achieve robust performance with a smaller parameter count,
excelling in reasoning, code generation, and mathematical problem-solving.
Maestro-10B inherits these strengths from its base model, Virtuoso-Lite, and
further enhances them through fine-tuning on the OpenOrca dataset. This combination
of a distilled base model and targeted fine-tuning makes Maestro-10B a powerful and
efficient language model.
</div>
<div class="model-composition">
<h4>Loss Graph</h4>
<img src="loss.png" alt="Model banner">
</div>
</div>
<div class="support-section">
<h2>Support & Community:</h2>
<div class="support-buttons">
<a href="https://buymeacoffee.com/suayptalha" target="_blank" class="button">
Buy me a coffee
</a>
<a href="https://discord.com/users/suaypt" target="_blank" class="button">
suayptalha - Discord
</a>
</div>
</div>
</div>
</div>
</body>
</html>