mradermacher
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README.md
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### vocab_type: -->
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<!-- ### tags: -->
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static quants of https://huggingface.co/werty1248/Mistral-Nemo-NT-Ko-12B-sft
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---
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base_model: werty1248/Mistral-Nemo-NT-Ko-12B-sft
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datasets:
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- 4DR1455/finance_questions
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- Aratako/Synthetic-JP-Conversations-Magpie-Nemotron-4-10k
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- Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k
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- Aratako/Synthetic-Japanese-Roleplay-NSFW-Claude-3.5s-10.5k-formatted
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- BCCard/BCCard-Finance-Kor-QnA
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- CarrotAI/ko-code-alpaca-QA
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- ChuGyouk/AI_healthcare_QA_samples_Sonnet3.5
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- DavidLanz/medical_instruction
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- Dusker/lawyer-llama
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- Gryphe/Sonnet3.5-Charcard-Roleplay
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- HAERAE-HUB/qarv-instruct-ko
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- HachiML/alpaca_jp_math
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- Magpie-Align/Magpie-Llama-3.1-Pro-MT-300K-v0.1
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- Magpie-Align/Magpie-Qwen2-Pro-200K-Chinese
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- beomi/KoAlpaca-v1.1a
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- codefuse-ai/Evol-instruction-66k
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- frankminors123/belle-math-zh
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- gbharti/wealth-alpaca_lora
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- iam-ajaymeena/Self-Instruct-Japanese-Elzya-13B
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- jihye-moon/LawQA-Ko
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- jondurbin/gutenberg-dpo-v0.1
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- junyeong-nero/kin_med_100K_edited
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- kyujinpy/KOR-OpenOrca-Platypus-v3
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- lavita/medical-qa-datasets
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- microsoft/orca-math-word-problems-200k
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- neural-bridge/rag-dataset-12000
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- p1atdev/ichikara-instruction
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- qiaojin/PubMedQA
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- shibing624/roleplay-zh-sharegpt-gpt4-data
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- team-hatakeyama-phase2/AutoMultiTurnByCalm3-22B-Corrected-reformatted
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- ymoslem/Law-StackExchange
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- zzunyang/LawQA_LawSee
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language:
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- en
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- ko
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- ja
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- zh
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library_name: transformers
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license: apache-2.0
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quantized_by: mradermacher
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---
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## About
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<!-- ### quantize_version: 2 -->
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<!-- ### output_tensor_quantised: 1 -->
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<!-- ### convert_type: hf -->
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<!-- ### vocab_type: -->
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<!-- ### tags: -->
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static quants of https://huggingface.co/werty1248/Mistral-Nemo-NT-Ko-12B-sft
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<!-- provided-files -->
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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.
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## Usage
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If you are unsure how to use GGUF files, refer to one of [TheBloke's
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READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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more details, including on how to concatenate multi-part files.
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## Provided Quants
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(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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| Link | Type | Size/GB | Notes |
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|:-----|:-----|--------:|:------|
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q2_K.gguf) | Q2_K | 4.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.IQ3_XS.gguf) | IQ3_XS | 5.4 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q3_K_S.gguf) | Q3_K_S | 5.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.IQ3_S.gguf) | IQ3_S | 5.7 | beats Q3_K* |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.IQ3_M.gguf) | IQ3_M | 5.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q3_K_M.gguf) | Q3_K_M | 6.2 | lower quality |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q3_K_L.gguf) | Q3_K_L | 6.7 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.IQ4_XS.gguf) | IQ4_XS | 6.9 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q4_K_S.gguf) | Q4_K_S | 7.2 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q4_K_M.gguf) | Q4_K_M | 7.6 | fast, recommended |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q5_K_S.gguf) | Q5_K_S | 8.6 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q5_K_M.gguf) | Q5_K_M | 8.8 | |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q6_K.gguf) | Q6_K | 10.2 | very good quality |
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| [GGUF](https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q8_0.gguf) | Q8_0 | 13.1 | fast, best quality |
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Here is a handy graph by ikawrakow comparing some lower-quality quant
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types (lower is better):
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![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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And here are Artefact2's thoughts on the matter:
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https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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## FAQ / Model Request
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See https://huggingface.co/mradermacher/model_requests for some answers to
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questions you might have and/or if you want some other model quantized.
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## Thanks
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I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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me use its servers and providing upgrades to my workstation to enable
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this work in my free time.
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<!-- end -->
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