base_model: AIDC-AI/Marco-Mini-Base
datasets:
- nvidia/Nemotron-CC-v2
- nvidia/Nemotron-Pretraining-SFT-v1
- nvidia/Nemotron-Pretraining-Specialized-v1
- nvidia/Nemotron-CC-v2.1
- allenai/dolmino-mix-1124
- nvidia/Nemotron-CC-Math-v1
- nvidia/OpenMathInstruct-2
- HuggingFaceTB/finemath
- LLM360/MegaMath
- open-thoughts/OpenThoughts3-1.2M
- opencsg/Fineweb-Edu-Chinese-V2.1
- HuggingFaceFW/fineweb-2
- allenai/dolma3_dolmino_mix-100B-1125
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
static quants of https://huggingface.co/AIDC-AI/Marco-Mini-Base
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Marco-Mini-Base-i1-GGUF
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 | 6.5 | |
| GGUF | Q3_K_S | 7.7 | |
| GGUF | Q3_K_M | 8.5 | lower quality |
| GGUF | Q3_K_L | 9.1 | |
| GGUF | IQ4_XS | 9.5 | |
| GGUF | Q4_K_S | 10.0 | fast, recommended |
| GGUF | Q4_K_M | 10.7 | fast, recommended |
| GGUF | Q5_K_S | 12.1 | |
| GGUF | Q5_K_M | 12.5 | |
| GGUF | Q6_K | 14.4 | very good quality |
| GGUF | Q8_0 | 18.6 | 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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.