base_model: Saxo/Linkbricks-Horizon-AI-Korean-Superb-22B
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
static quants of https://huggingface.co/Saxo/Linkbricks-Horizon-AI-Korean-Superb-22B
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Korean-Superb-22B-i1-GGUF
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 | Q2_K | 8.4 | |
| GGUF | Q3_K_S | 9.7 | |
| GGUF | Q3_K_M | 10.9 | lower quality |
| GGUF | Q3_K_L | 11.8 | |
| GGUF | IQ4_XS | 12.1 | |
| GGUF | Q4_K_S | 12.8 | fast, recommended |
| GGUF | Q4_K_M | 13.4 | fast, recommended |
| GGUF | Q5_K_S | 15.4 | |
| GGUF | Q5_K_M | 15.8 | |
| GGUF | Q6_K | 18.4 | very good quality |
| GGUF | Q8_0 | 23.7 | 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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.