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base_model:
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- mlabonne/AlphaMonarch-7B
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- Syed-Hasan-8503/Tess-Coder-7B-Mistral-v1.0
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---
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# MonarchCoder-MoE-2x7B
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MonarchCoder-MoE-2x7B is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
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* [Syed-Hasan-8503/Tess-Coder-7B-Mistral-v1.0](https://huggingface.co/Syed-Hasan-8503/Tess-Coder-7B-Mistral-v1.0)
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## 🧩 Configuration
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```yaml
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base_model:
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- mlabonne/AlphaMonarch-7B
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- Syed-Hasan-8503/Tess-Coder-7B-Mistral-v1.0
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language:
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- en
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library_name: transformers
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---
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# MonarchCoder-MoE-2x7B
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MonarchCoder-MoE-2x7B is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
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* [Syed-Hasan-8503/Tess-Coder-7B-Mistral-v1.0](https://huggingface.co/Syed-Hasan-8503/Tess-Coder-7B-Mistral-v1.0)
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The main aim behind creating this model is to create a model that performs well in reasoning, conversation, and coding. AlphaMonarch pperforms amazing on reasoning and conversation tasks. Merging AlphaMonarch with a coding model yielded MonarchCoder-2x7B which performs better on OpenLLM, Nous, and HumanEval benchmark.
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## 🧩 Configuration
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```yaml
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