Update README.md
Browse filesThanks for the additional quants, [DAN™](https://huggingface.co/dranger003)!
README.md
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- HF: wolfram/miquliz-120b-v2.0
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- GGUF: [Q2_K | IQ3_XXS | Q4_K_M | Q5_K_M](https://huggingface.co/wolfram/miquliz-120b-v2.0-GGUF)
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- EXL2: [2.4bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-2.4bpw-h6-exl2) | [2.65bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-2.65bpw-h6-exl2) | [3.0bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-3.0bpw-h6-exl2) | [3.5bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-3.5bpw-h6-exl2) | [4.0bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-4.0bpw-h6-exl2) | [5.0bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-5.0bpw-h6-exl2)
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This is v2.0 of a 120b frankenmerge created by interleaving layers of [miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) with [lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf) using [mergekit](https://github.com/cg123/mergekit). Better than v1.0 thanks to the improved recipe adapted from [TheProfessor-155b](https://huggingface.co/abacusai/TheProfessor-155b) by [Eric Hartford](https://erichartford.com/), it is now achieving top rank with double perfect scores in [my LLM comparisons/tests](https://www.reddit.com/r/LocalLLaMA/search?q=author%3AWolframRavenwolf+Comparison%2FTest&sort=new&t=all).
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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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Also available: [miqu-1-120b](https://huggingface.co/wolfram/miqu-1-120b) – Miquliz's older, purer sister; only Miqu, inflated to 120B.
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## Model Details
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- HF: wolfram/miquliz-120b-v2.0
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- GGUF: [IQ2_XS | IQ2_XXS | IQ3_XXS](https://huggingface.co/dranger003/miquliz-120b-v2.0-iMat.GGUF) | [Q2_K | IQ3_XXS | Q4_K_M | Q5_K_M](https://huggingface.co/wolfram/miquliz-120b-v2.0-GGUF) | [Q8_0](https://huggingface.co/dranger003/miquliz-120b-v2.0-iMat.GGUF)
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- EXL2: [2.4bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-2.4bpw-h6-exl2) | [2.65bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-2.65bpw-h6-exl2) | [3.0bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-3.0bpw-h6-exl2) | [3.5bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-3.5bpw-h6-exl2) | [4.0bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-4.0bpw-h6-exl2) | [5.0bpw](https://huggingface.co/wolfram/miquliz-120b-v2.0-5.0bpw-h6-exl2)
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This is v2.0 of a 120b frankenmerge created by interleaving layers of [miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) with [lzlv_70b_fp16_hf](https://huggingface.co/lizpreciatior/lzlv_70b_fp16_hf) using [mergekit](https://github.com/cg123/mergekit). Better than v1.0 thanks to the improved recipe adapted from [TheProfessor-155b](https://huggingface.co/abacusai/TheProfessor-155b) by [Eric Hartford](https://erichartford.com/), it is now achieving top rank with double perfect scores in [my LLM comparisons/tests](https://www.reddit.com/r/LocalLLaMA/search?q=author%3AWolframRavenwolf+Comparison%2FTest&sort=new&t=all).
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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 additional quants, [DAN™](https://huggingface.co/dranger003)!
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Also available: [miqu-1-120b](https://huggingface.co/wolfram/miqu-1-120b) – Miquliz's older, purer sister; only Miqu, inflated to 120B.
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## Model Details
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