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---
base_model:
- CallComply/gemma-2-27b-it
- TheDrummer/Big-Tiger-Gemma-27B-v1
- migtissera/Tess-v2.5-Gemma-2-27B-alpha
library_name: transformers
tags:
- mergekit
- merge
---
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<h1>G2-MS-Nyxora-27b</h1>
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<div class="info">
<img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/rqcAEjzvLpQwu2Cg3g1hH.png" alt="Model Image">
<p>Now that the cute anime girl has your attention.</p>
<p><strong>Creator:</strong> <a href="https://huggingface.co/Steelskull" target="_blank">SteelSkull</a></p>
<h1>About G2-MS-Nyxora-27b:</h1>
<pre><code><strong>Model Name Legend =</strong>
"G2 = Gemma 2"
"MS = Model_stock"</code></pre>
<p>This model represents an experimental foray into 27b models. Feedback is welcome for further improvements.</p>
<p>G2-MS-Nyxora-27b combines multiple models' strengths to provide a versatile assistant for various tasks, including general use, storytelling, roleplay, and mature content.</p>
<p>The Model_stock merge method ensures the model remains focused, tailored, and high-quality.</p>
<h2>Quants:</h2>
<p>Will add once found</p>
<h2>Config:</h2>
<pre><code>MODEL_NAME = "G2-MS-Nyxora-27b"
yaml_config = """
base_model: google/gemma-2-27b-it
merge_method: model_stock
dtype: bfloat16
models:
- model: TheDrummer/Big-Tiger-Gemma-27B-v1
- model: migtissera/Tess-v2.5-Gemma-2-27B-alpha
"""</code></pre>
<h4>Template:</h4>
<pre><code><start_of_turn>user
{{ if .System }}{{ .System }} {{ end }}{{ .Prompt }}<end_of_turn>
<start_of_turn>model
{{ .Response }}<end_of_turn></code></pre>
<h4>Source Model Details:</h4>
<p><strong>TheDrummer/Big-Tiger-Gemma-27B-v1:</strong><br>
A decensored version of the Gemma 27B model.
</p>
<p><strong>migtissera/Tess-v2.5-Gemma-2-27B-alpha:</strong><br>
The latest state-of-the-art model in the Tess series, Tess-v2.5.2, offers significant improvements in reasoning, coding, and mathematics. It ranks #1 on the MMLU benchmark among open weight models and outperforms several frontier closed models.
</p>
<p><strong>Gemma-2-27b-it:</strong><br>
A lightweight, state-of-the-art model from Google, well-suited for various text generation tasks. Its small size allows deployment in resource-limited environments, fostering AI innovation for all.
</p>
<h4>Merge Method Details:</h4>
<p>Model_stock Uses some neat geometric properties of fine tuned models to compute good weights for linear interpolation.</p>
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