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Update README.md (#1)

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- Update README.md (acdb64c65524fb8c876e399c32008ce603019f46)


Co-authored-by: Wolfram Ravenwolf <[email protected]>

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  1. README.md +4 -4
README.md CHANGED
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6303ca537373aacccd85d8a7/LxO9j7OykuabKLYQHIodG.jpeg)
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- - HF: wolfram/miqu-1-103b
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- - GGUF: [mradermacher's Q2_K | Q3_K_S | Q3_K_M | Q4_K_M | Q6_K | Q8_0](https://huggingface.co/mradermacher/miqu-1-103b-GGUF)
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- - EXL2: 🔜
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  This is a 103b 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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  Thanks for the support, [CopilotKit](https://github.com/CopilotKit/CopilotKit) - the open-source platform for building in-app AI Copilots into any product, with any LLM model. Check out their GitHub.
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- Thanks for the GGUF quants, [Michael Radermacher](https://huggingface.co/mradermacher)!
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  Also available:
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  ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6303ca537373aacccd85d8a7/LxO9j7OykuabKLYQHIodG.jpeg)
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+ - HF: [wolfram/miqu-1-103b](https://huggingface.co/wolfram/miqu-1-103b)
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+ - GGUF: mradermacher's [static quants](https://huggingface.co/mradermacher/miqu-1-103b-GGUF) | [weighted/imatrix quants](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF)
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+ - EXL2: LoneStriker's [2.4bpw](https://huggingface.co/LoneStriker/miqu-1-103b-2.4bpw-h6-exl2) | [3.0bpw](https://huggingface.co/LoneStriker/miqu-1-103b-3.0bpw-h6-exl2) | [3.5bpw](https://huggingface.co/LoneStriker/miqu-1-103b-3.5bpw-h6-exl2)
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  This is a 103b 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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  Thanks for the support, [CopilotKit](https://github.com/CopilotKit/CopilotKit) - the open-source platform for building in-app AI Copilots into any product, with any LLM model. Check out their GitHub.
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+ Thanks for the quants, [Michael Radermacher](https://huggingface.co/mradermacher) and [Lone Striker](https://huggingface.co/LoneStriker)!
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  Also available:
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