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---
base_model:
- 152334H/miqu-1-70b-sf
- lizpreciatior/lzlv_70b_fp16_hf
language:
- en
library_name: transformers
license: other
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About
weighted/imatrix quants of https://huggingface.co./wolfram/miquliz-120b-v2.0
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static quants are available at https://huggingface.co./mradermacher/miquliz-120b-v2.0-GGUF
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co./TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.
## Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-IQ1_S.gguf) | i1-IQ1_S | 25.7 | for the desperate |
| [GGUF](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 32.2 | |
| [GGUF](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-IQ2_XS.gguf) | i1-IQ2_XS | 35.8 | |
| [GGUF](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q2_K.gguf) | i1-Q2_K | 44.6 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 47.3 | fast, lower quality |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_XS.gguf.split-aa) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_XS.gguf.split-ab) | i1-Q3_K_XS | 49.3 | |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_S.gguf.split-aa) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_S.gguf.split-ab) | i1-Q3_K_S | 52.2 | IQ3_XS probably better |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_M.gguf.split-aa) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_M.gguf.split-ab) | i1-Q3_K_M | 58.2 | IQ3_S probably better |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_L.gguf.split-aa) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q3_K_L.gguf.split-ab) | i1-Q3_K_L | 63.4 | IQ3_M probably better |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q4_K_S.gguf.split-aa) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q4_K_S.gguf.split-ab) | i1-Q4_K_S | 68.7 | almost as good as Q4_K_M |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q4_K_M.gguf.split-aa) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q4_K_M.gguf.split-ab) | i1-Q4_K_M | 72.6 | fast, medium quality |
| [PART 1](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co./mradermacher/miquliz-120b-v2.0-i1-GGUF/resolve/main/miquliz-120b-v2.0.i1-Q5_K_M.gguf.part2of2) | i1-Q5_K_M | 85.4 | best weighted quant |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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