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---
base_model: werty1248/Mistral-Nemo-NT-Ko-12B-dpo
datasets:
- zake7749/kyara-chinese-preference-rl-dpo-s0-30K
- sionic/ko-dpo-mix-7k-trl-style
- kuotient/orca-math-korean-dpo-pairs
- HuggingFaceH4/ultrafeedback_binarized
language:
- en
- ko
- ja
- zh
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
---
## About
<!-- ### quantize_version: 2 -->
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<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/werty1248/Mistral-Nemo-NT-Ko-12B-dpo
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static quants are available at https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-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/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-IQ2_M.gguf) | i1-IQ2_M | 4.5 | |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-Q2_K.gguf) | i1-Q2_K | 4.9 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 5.0 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-IQ3_M.gguf) | i1-IQ3_M | 5.8 | |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-Q3_K_M.gguf) | i1-Q3_K_M | 6.2 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-IQ4_XS.gguf) | i1-IQ4_XS | 6.8 | |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-IQ4_NL.gguf) | i1-IQ4_NL | 7.2 | prefer IQ4_XS |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-Q4_K_S.gguf) | i1-Q4_K_S | 7.2 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-Q4_K_M.gguf) | i1-Q4_K_M | 7.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-dpo-i1-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-dpo.i1-Q6_K.gguf) | i1-Q6_K | 10.2 | practically like static Q6_K |
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
## FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.
## 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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
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