---
exported_from: Noodlz/QueenLiz-120B
language:
- en
library_name: transformers
quantized_by: mradermacher
---
## About

static quants of https://huggingface.co/Noodlz/QueenLiz-120B

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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## 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/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q2_K.gguf) | Q2_K | 44.6 |  |
| [PART 1](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.IQ3_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.IQ3_S.gguf.part2of2) | IQ3_S | 52.4 | beats Q3_K* |
| [PART 1](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q3_K_M.gguf.part2of2) | Q3_K_M | 58.2 | lower quality |
| [PART 1](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q4_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q4_0.gguf.part2of2) | Q4_0 | 68.2 |  |
| [PART 1](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q4_K_S.gguf.part2of2) | Q4_K_S | 68.7 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q8_0.gguf.part1of3) [PART 2](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q8_0.gguf.part2of3) [PART 3](https://huggingface.co/mradermacher/QueenLiz-120B-GGUF/resolve/main/QueenLiz-120B.Q8_0.gguf.part3of3) | Q8_0 | 128.2 | fast, best quality |


Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

## Thanks

I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

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