---
base_model: AIDC-AI/Marco-Nano-Instruct
datasets:
- allenai/Dolci-Instruct-SFT
- nvidia/Nemotron-Cascade-2-SFT-Data
- nvidia/Nemotron-RL-instruction_following
- nvidia/Nemotron-RL-instruction_following-structured_outputs
- nvidia/Nemotron-RL-ReasoningGym-v1
- nvidia/Nemotron-RL-knowledge-mcqa
- nvidia/Nemotron-Cascade-RL-RLHF
- BytedTsinghua-SIA/DAPO-Math-17k
- Skywork/Skywork-OR1-RL-Data
- nvidia/Nemotron-SFT-Multilingual-v1
language:
- en
- zh
- ar
- de
- es
- fr
- ko
- ja
- pt
- tr
- id
- it
- nl
- pl
- ru
- vi
- th
- he
- uk
- ms
- bn
- cs
- ur
- kk
- el
- ro
- hu
- ne
- az
library_name: transformers
license: apache-2.0
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
- moe
- mixture-of-experts
- multilingual
- upcycling
---
## About

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<!-- ### quants:  Q2_K IQ3_M Q4_K_S IQ3_XXS Q3_K_M small-IQ4_NL Q4_K_M IQ2_M Q6_K IQ4_XS Q2_K_S IQ1_M Q3_K_S IQ2_XXS Q3_K_L IQ2_XS Q5_K_S IQ2_S IQ1_S Q5_K_M Q4_0 IQ3_XS Q4_1 IQ3_S -->
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weighted/imatrix quants of https://huggingface.co/AIDC-AI/Marco-Nano-Instruct

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***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Marco-Nano-Instruct-i1-GGUF).***

static quants are available at https://huggingface.co/mradermacher/Marco-Nano-Instruct-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/Marco-Nano-Instruct-i1-GGUF/resolve/main/Marco-Nano-Instruct.imatrix.gguf) | imatrix | 0.2 | imatrix file (for creating your own quants) |
| [GGUF](https://huggingface.co/mradermacher/Marco-Nano-Instruct-i1-GGUF/resolve/main/Marco-Nano-Instruct.i1-Q2_K.gguf) | i1-Q2_K | 3.4 | IQ3_XXS probably better |

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.

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