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Ateron/Gemma-4-AssGuard-31B
Gemma-4-AssGuard-31B is a text generation model from Ateron. Use it when you need the model to write or continue text. The card lists the license as apache-2.0.
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Downloads · 30 days
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.safetensors62.5 GB · 100%
From the Hugging Face model README
This is a thing I did for fun, experimenting here and there. But to my surprise this stuff can hit the mark and generate very funny outcomes. So I decided to let this model to live. Might steal your attention for several swipes.
<h3 style="color: #1b76aa; margin-top: 15px;"> Settings</h3>I suggest to use high min_p from around 0.15-0.20. That's it all others is up to your experiments.
<h3 style="color: #1b76aa; margin-top: 15px;">♻️ Mergekit Configuration</h3>Below is the exact mergekit_config.yml recipe used to synthesize this model:
The place where the gods and warriors lives.
<details> <summary>dare_ties Recipe 1</summary>merge_method: dare_ties
base_model: F:\AI\Merge\Gemma-4-it
tokenizer_source: union
dtype: bfloat16
parameters:
lambda: 1.0
models:
- model: F:\AI\Merge\G4-Gutenberg
parameters:
density: [0.70, 0.70, 0.60, 0.60, 0.70]
weight:
- filter: mlp
value: [0.40, 0.45, 0.40, 0.40, 0.40]
- filter: self_attn
value: [0.30, 0.40, 0.50, 0.50, 0.50]
- value: [0.50, 0.50, 0.50, 0.50, 0.50]
- model: F:\AI\Merge\Pantheon-Reasoning-31B-1.1
parameters:
density: [0.30, 0.30, 0.40, 0.35, 0.25]
weight:
- filter: mlp
value: [0.40, 0.50, 0.40, 0.30, 0.10]
- filter: self_attn
value: [0.40, 0.35, 0.35, 0.30, 0.10]
- value: [0.30, 0.30, 0.40, 0.30, 0.10]
</details>
The headmaster himself!
<details> <summary>model_stock Recipe 2</summary>models:
- model: F:\AI\Merge\Equinox
- model: F:\AI\Merge\Gemma-4-31B-storymaxxed2
- model: F:\AI\Merge\GarnetV2
merge_method: model_stock
base_model: F:\AI\Merge\Gemma-4-it
dtype: bfloat16
tokenizer_source: union
</details>
Preparation becomes!
<details> <summary>dare_ties Recipe 3</summary>merge_method: dare_ties
base_model: F:\AI\Merge\Gemma-4-it
tokenizer_source: union
dtype: bfloat16
parameters:
lambda: 1.0
models:
- model: F:\AI\Merge\Asgard
parameters:
density: [0.70, 0.70, 0.70, 0.70, 0.70]
weight:
- filter: mlp
value: [0.50, 0.50, 0.50, 0.50, 0.50]
- filter: self_attn
value: [0.40, 0.40, 0.40, 0.40, 0.40]
- value: [0.50, 0.50, 0.50, 0.50, 0.50]
- model: F:\AI\Merge\Odin
parameters:
density: [0.20, 0.30, 0.40, 0.30, 0.10]
weight:
- filter: mlp
value: [0.30, 0.40, 0.40, 0.40, 0.10]
- filter: self_attn
value: [0.30, 0.30, 0.30, 0.30, 0.10]
- value: [0.20, 0.30, 0.30, 0.20, 0.10]
</details>
<h2 style="color: #1b76aa; border-bottom: 1px solid #13455c; padding-bottom: 8px; margin-top: 30px;">🤝 Special Thanks</h2>
<ul style="color: #e2e4e9; line-height: 1.6;">
<li><strong>Google DeepMind:</strong> For providing the base model.</li>
<li><strong>The Open-Source Community:</strong> Creators and all their fine-tuned models that were used in the merge.</li>
<li><strong>Mergekit Fork:</strong> Zerofata - For making mergekit work.</li>
<li><strong>To Nimbz:</strong> <a href="https://huggingface.co/Nimbz" style="color: #1b76aa; text-decoration: none;">This cat</a> for being a smart fella and assisting with advices.</li>
</ul>
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