--- base_model: Saxo/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B 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 weighted/imatrix quants of https://huggingface.co/Saxo/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B static quants are available at https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-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-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ1_S.gguf) | i1-IQ1_S | 4.9 | for the desperate | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ1_M.gguf) | i1-IQ1_M | 5.4 | mostly desperate | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 6.1 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ2_XS.gguf) | i1-IQ2_XS | 6.7 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ2_S.gguf) | i1-IQ2_S | 7.1 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ2_M.gguf) | i1-IQ2_M | 7.7 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q2_K_S.gguf) | i1-Q2_K_S | 7.8 | very low quality | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q2_K.gguf) | i1-Q2_K | 8.4 | IQ3_XXS probably better | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 8.7 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ3_XS.gguf) | i1-IQ3_XS | 9.3 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q3_K_S.gguf) | i1-Q3_K_S | 9.7 | IQ3_XS probably better | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ3_S.gguf) | i1-IQ3_S | 9.8 | beats Q3_K* | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ3_M.gguf) | i1-IQ3_M | 10.2 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q3_K_M.gguf) | i1-Q3_K_M | 10.9 | IQ3_S probably better | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q3_K_L.gguf) | i1-Q3_K_L | 11.8 | IQ3_M probably better | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-IQ4_XS.gguf) | i1-IQ4_XS | 12.0 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q4_0.gguf) | i1-Q4_0 | 12.7 | fast, low quality | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q4_K_S.gguf) | i1-Q4_K_S | 12.8 | optimal size/speed/quality | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q4_K_M.gguf) | i1-Q4_K_M | 13.4 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q4_1.gguf) | i1-Q4_1 | 14.0 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q5_K_S.gguf) | i1-Q5_K_S | 15.4 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q5_K_M.gguf) | i1-Q5_K_M | 15.8 | | | [GGUF](https://huggingface.co/mradermacher/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B-i1-GGUF/resolve/main/Linkbricks-Horizon-AI-Japanese-Superb-V1-22B.i1-Q6_K.gguf) | i1-Q6_K | 18.4 | 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.