Update README.md

Thanks for the additional quants, [DAN™](https://huggingface.co/dranger003), [Knut Jägersberg](https://huggingface.co/KnutJaegersberg), and [Michael Radermacher](https://huggingface.co/mradermacher)!

README.md

@@ -18,7 +18,11 @@ tags:
 ![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6303ca537373aacccd85d8a7/vmCAhJCpF0dITtCVxlYET.jpeg)
 
 - HF: [wolfram/miquliz-120b-v2.0](https://huggingface.co/wolfram/miquliz-120b-v2.0)
-- 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 | [Q8_0](https://huggingface.co/dranger003/miquliz-120b-v2.0-iMat.GGUF)
+- GGUF: Q2_K | IQ3_XXS | Q4_K_M | Q5_K_M
+  - [dranger003's IQ2_XS | IQ2_XXS | IQ3_XXS | Q8_0](https://huggingface.co/dranger003/miquliz-120b-v2.0-iMat.GGUF)
+  - [KnutJaegersberg's IQ2_XS](https://huggingface.co/KnutJaegersberg/2-bit-LLMs)
+  - [mradermacher's i1-IQ1_S – i1-Q5_K_M](https://huggingface.co/mradermacher/miquliz-120b-v2.0-i1-GGUF)
+  - [mradermacher's Q2_K – Q8_0](https://huggingface.co/mradermacher/miquliz-120b-v2.0-GGUF)
 - 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)
 
 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).
@@ -27,7 +31,7 @@ Inspired by [goliath-120b](https://huggingface.co/alpindale/goliath-120b).
 
 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.
 
-Thanks for the additional quants, [DAN™](https://huggingface.co/dranger003)!
+Thanks for the additional quants, [DAN™](https://huggingface.co/dranger003), [Knut Jägersberg](https://huggingface.co/KnutJaegersberg), and [Michael Radermacher](https://huggingface.co/mradermacher)!
 
 Also available: [miqu-1-120b](https://huggingface.co/wolfram/miqu-1-120b) – Miquliz's older, purer sister; only Miqu, inflated to 120B.