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---
base_model: Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B
datasets:
- Saxo/ko_cn_translation_tech_social_science_linkbricks_single_dataset
- Saxo/ko_jp_translation_tech_social_science_linkbricks_single_dataset
- Saxo/en_ko_translation_tech_science_linkbricks_single_dataset_with_prompt_text_huggingface
- Saxo/en_ko_translation_social_science_linkbricks_single_dataset_with_prompt_text_huggingface
- Saxo/ko_aspect_sentiment_sns_mall_sentiment_linkbricks_single_dataset_with_prompt_text_huggingface
- Saxo/ko_summarization_linkbricks_single_dataset_with_prompt_text_huggingface
- Saxo/OpenOrca_cleaned_kor_linkbricks_single_dataset_with_prompt_text_huggingface
- Saxo/ko_government_qa_total_linkbricks_single_dataset_with_prompt_text_huggingface_sampled
- Saxo/ko-news-corpus-1
- Saxo/ko-news-corpus-2
- Saxo/ko-news-corpus-3
- Saxo/ko-news-corpus-4
- Saxo/ko-news-corpus-5
- Saxo/ko-news-corpus-6
- Saxo/ko-news-corpus-7
- Saxo/ko-news-corpus-8
- Saxo/ko-news-corpus-9
- maywell/ko_Ultrafeedback_binarized
- youjunhyeok/ko-orca-pair-and-ultrafeedback-dpo
- lilacai/glaive-function-calling-v2-sharegpt
- kuotient/gsm8k-ko
language:
- ko
- en
- jp
- cn
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
---
## About
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static quants of https://huggingface.co/Saxo/Linkbricks-Horizon-AI-Korean-Superb-27B
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-i1-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/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q2_K.gguf) | Q2_K | 10.5 | |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q3_K_S.gguf) | Q3_K_S | 12.3 | |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q3_K_M.gguf) | Q3_K_M | 13.5 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q3_K_L.gguf) | Q3_K_L | 14.6 | |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.IQ4_XS.gguf) | IQ4_XS | 15.0 | |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q4_K_S.gguf) | Q4_K_S | 15.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q4_K_M.gguf) | Q4_K_M | 16.7 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q5_K_S.gguf) | Q5_K_S | 19.0 | |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q5_K_M.gguf) | Q5_K_M | 19.5 | |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q6_K.gguf) | Q6_K | 22.4 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-27B-GGUF/resolve/main/Linkbricks-Horizon-AI-Korean-Superb-27B.Q8_0.gguf) | Q8_0 | 29.0 | fast, best quality |
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
## 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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