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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6303ca537373aacccd85d8a7/LxO9j7OykuabKLYQHIodG.jpeg)
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- * EXL2: [2.4bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-2.4bpw-h6-exl2) | [2.65bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-2.65bpw-h6-exl2) | [3.0bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-3.0bpw-h6-exl2) | [4.0bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-4.0bpw-h6-exl2) | [5.0bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-5.0bpw-h6-exl2)
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- * GGUF: [Q2_K-Q5_K_M](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-GGUF/) | [IQ3_XXS](https://huggingface.co/wolfram/miqu-1-120b-GGUF)
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  This is a 120b frankenmerge of [miqu-1-70b](https://huggingface.co/miqudev/miqu-1-70b) created by interleaving layers of [miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) with itself using [mergekit](https://github.com/cg123/mergekit).
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  ## Model Details
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- * Max Context: 32764 tokens (kept the weird number from the original/base model)
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- * Layers: 140
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  ### Prompt template: Mistral
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  ### Models Merged
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  The following models were included in the merge:
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- * [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf)
 
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  ### Configuration
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  ## Credits & Special Thanks
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- * original (unreleased) model: [mistralai (Mistral AI_)](https://huggingface.co/mistralai)
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- * leaked model: [miqudev/miqu-1-70b](https://huggingface.co/miqudev/miqu-1-70b)
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- * f16 model: [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf)
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- * mergekit: [arcee-ai/mergekit: Tools for merging pretrained large language models.](https://github.com/arcee-ai/mergekit)
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- * mergekit_config.yml: [nsfwthrowitaway69/Venus-120b-v1.2](https://huggingface.co/nsfwthrowitaway69/Venus-120b-v1.2)
 
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  ### Support
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- * [My Ko-fi page](https://ko-fi.com/wolframravenwolf) if you'd like to tip me to say thanks or request specific models to be tested or merged with priority. Also consider supporting your favorite model creators, quantizers, or frontend/backend devs if you can afford to do so. They deserve it!
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  ## Disclaimer
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6303ca537373aacccd85d8a7/LxO9j7OykuabKLYQHIodG.jpeg)
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+ - EXL2: [2.4bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-2.4bpw-h6-exl2) | [2.65bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-2.65bpw-h6-exl2) | [3.0bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-3.0bpw-h6-exl2) | [4.0bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-4.0bpw-h6-exl2) | [5.0bpw](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-5.0bpw-h6-exl2)
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+ - GGUF: [Q2_K-Q5_K_M](https://huggingface.co/LoneStriker/wolfram_miqu-1-120b-GGUF/) | [IQ3_XXS](https://huggingface.co/wolfram/miqu-1-120b-GGUF)
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  This is a 120b frankenmerge of [miqu-1-70b](https://huggingface.co/miqudev/miqu-1-70b) created by interleaving layers of [miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) with itself using [mergekit](https://github.com/cg123/mergekit).
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  ## Model Details
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+ - Max Context: 32764 tokens (kept the weird number from the original/base model)
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+ - Layers: 140
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  ### Prompt template: Mistral
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  ### Models Merged
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  The following models were included in the merge:
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+ - [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf)
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  ### Configuration
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  ## Credits & Special Thanks
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+ - original (unreleased) model: [mistralai (Mistral AI_)](https://huggingface.co/mistralai)
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+ - ⭐⭐⭐ **[Use their newer, better, official models here!](https://console.mistral.ai/)** ⭐⭐⭐
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+ - leaked model: [miqudev/miqu-1-70b](https://huggingface.co/miqudev/miqu-1-70b)
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+ - f16 model: [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf)
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+ - mergekit: [arcee-ai/mergekit: Tools for merging pretrained large language models.](https://github.com/arcee-ai/mergekit)
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+ - mergekit_config.yml: [nsfwthrowitaway69/Venus-120b-v1.2](https://huggingface.co/nsfwthrowitaway69/Venus-120b-v1.2)
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  ### Support
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+ - [My Ko-fi page](https://ko-fi.com/wolframravenwolf) if you'd like to tip me to say thanks or request specific models to be tested or merged with priority. Also consider supporting your favorite model creators, quantizers, or frontend/backend devs if you can afford to do so. They deserve it!
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  ## Disclaimer
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