|
--- |
|
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 |
|
|
|
<!-- ### quantize_version: 2 --> |
|
<!-- ### output_tensor_quantised: 1 --> |
|
<!-- ### convert_type: hf --> |
|
<!-- ### vocab_type: --> |
|
<!-- ### tags: --> |
|
static quants of https://huggingface.co/werty1248/Mistral-Nemo-NT-Ko-12B-sft |
|
|
|
<!-- provided-files --> |
|
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Mistral-Nemo-NT-Ko-12B-sft-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/Mistral-Nemo-NT-Ko-12B-sft-GGUF/resolve/main/Mistral-Nemo-NT-Ko-12B-sft.Q2_K.gguf) | Q2_K | 4.9 | | |
|
| [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 | | |
|
| [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 | | |
|
| [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* | |
|
| [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 | | |
|
| [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 | |
|
| [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 | | |
|
| [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 | | |
|
| [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 | |
|
| [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 | |
|
| [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 | | |
|
| [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 | | |
|
| [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 | |
|
| [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 | |
|
|
|
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. |
|
|
|
<!-- end --> |
|
|
