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Mistral-Nemo-NT-Ko-12B-sft-GGUF

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metadata
base_model: werty1248/Mistral-Nemo-NT-Ko-12B-sft
datasets:
  - 4DR1455/finance_questions
  - Aratako/Synthetic-JP-Conversations-Magpie-Nemotron-4-10k
  - Aratako/Synthetic-JP-EN-Coding-Dataset-Magpie-69k
  - Aratako/Synthetic-Japanese-Roleplay-NSFW-Claude-3.5s-10.5k-formatted
  - BCCard/BCCard-Finance-Kor-QnA
  - CarrotAI/ko-code-alpaca-QA
  - ChuGyouk/AI_healthcare_QA_samples_Sonnet3.5
  - DavidLanz/medical_instruction
  - Dusker/lawyer-llama
  - Gryphe/Sonnet3.5-Charcard-Roleplay
  - HAERAE-HUB/qarv-instruct-ko
  - HachiML/alpaca_jp_math
  - Magpie-Align/Magpie-Llama-3.1-Pro-MT-300K-v0.1
  - Magpie-Align/Magpie-Qwen2-Pro-200K-Chinese
  - beomi/KoAlpaca-v1.1a
  - codefuse-ai/Evol-instruction-66k
  - frankminors123/belle-math-zh
  - gbharti/wealth-alpaca_lora
  - iam-ajaymeena/Self-Instruct-Japanese-Elzya-13B
  - jihye-moon/LawQA-Ko
  - jondurbin/gutenberg-dpo-v0.1
  - junyeong-nero/kin_med_100K_edited
  - kyujinpy/KOR-OpenOrca-Platypus-v3
  - lavita/medical-qa-datasets
  - microsoft/orca-math-word-problems-200k
  - neural-bridge/rag-dataset-12000
  - p1atdev/ichikara-instruction
  - qiaojin/PubMedQA
  - shibing624/roleplay-zh-sharegpt-gpt4-data
  - team-hatakeyama-phase2/AutoMultiTurnByCalm3-22B-Corrected-reformatted
  - ymoslem/Law-StackExchange
  - zzunyang/LawQA_LawSee
language:
  - en
  - ko
  - ja
  - zh
library_name: transformers
license: apache-2.0
quantized_by: mradermacher

About

static quants of https://huggingface.co/werty1248/Mistral-Nemo-NT-Ko-12B-sft

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.

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 4.9
GGUF IQ3_XS 5.4
GGUF Q3_K_S 5.6
GGUF IQ3_S 5.7 beats Q3_K*
GGUF IQ3_M 5.8
GGUF Q3_K_M 6.2 lower quality
GGUF Q3_K_L 6.7
GGUF IQ4_XS 6.9
GGUF Q4_K_S 7.2 fast, recommended
GGUF Q4_K_M 7.6 fast, recommended
GGUF Q5_K_S 8.6
GGUF Q5_K_M 8.8
GGUF Q6_K 10.2 very good quality
GGUF Q8_0 13.1 fast, best quality

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.