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README.md
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---
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license: apache-2.0
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tags:
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- merge
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- mergekit
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- lazymergekit
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- vicgalle/Configurable-Llama-3.1-8B-Instruct
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- bunnycore/HyperLlama-3.1-8B
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- ValiantLabs/Llama3.1-8B-ShiningValiant2
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---
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[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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# QuantFactory/HyperLlama3.1-v2-GGUF
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This is quantized version of [bunnycore/HyperLlama3.1-v2](https://huggingface.co/bunnycore/HyperLlama3.1-v2) created using llama.cpp
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# Original Model Card
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# HyperLlama3.1-v2
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HyperLlama3.1-v2 is a merge of the following models using [mergekit](https://github.com/cg123/mergekit):
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* [vicgalle/Configurable-Llama-3.1-8B-Instruct](https://huggingface.co/vicgalle/Configurable-Llama-3.1-8B-Instruct)
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* [bunnycore/HyperLlama-3.1-8B](https://huggingface.co/bunnycore/HyperLlama-3.1-8B)
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* [ValiantLabs/Llama3.1-8B-ShiningValiant2](https://huggingface.co/ValiantLabs/Llama3.1-8B-ShiningValiant2)
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: vicgalle/Configurable-Llama-3.1-8B-Instruct
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parameters:
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weight: 1
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layer_range: [0, 32]
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- model: bunnycore/HyperLlama-3.1-8B
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parameters:
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weight: 0.9
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layer_range: [0, 32]
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- model: ValiantLabs/Llama3.1-8B-ShiningValiant2
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parameters:
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weight: 0.6
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layer_range: [0, 32]
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merge_method: task_arithmetic
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base_model: bunnycore/HyperLlama-3.1-8B
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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```
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