base_model: Loom-Labs/Apollo-1-4B
language:
- en
- fr
- pt
- de
- ro
- sv
- da
- bg
- ru
- cs
- el
- uk
- es
- nl
- sk
- hr
- pl
- lt
- nb
- nn
- fa
- sl
- gu
- lv
- it
- oc
- ne
- mr
- be
- sr
- lb
- vec
- as
- cy
- szl
- ast
- hne
- awa
- mai
- bho
- sd
- ga
- fo
- hi
- pa
- bn
- or
- tg
- yi
- lmo
- lij
- scn
- fur
- sc
- gl
- ca
- is
- sq
- li
- prs
- af
- mk
- si
- ur
- mag
- bs
- hy
- zh
- yue
- my
- ar
- he
- mt
- id
- ms
- tl
- ceb
- jv
- su
- min
- ban
- pag
- ilo
- war
- ta
- te
- kn
- ml
- tr
- az
- uz
- kk
- ba
- tt
- th
- lo
- fi
- et
- hu
- vi
- km
- ja
- ko
- ka
- eu
- ht
- pap
- kea
- tpi
- sw
library_name: transformers
license: other
license_link: https://huggingface.co/apexion-ai/Nous-V1-8B/blob/main/LICENSE.md
license_name: anvdl-1.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- qwen3
About
weighted/imatrix quants of https://huggingface.co/Loom-Labs/Apollo-1-4B
For a convenient overview and download list, visit our model page for this model.
static quants are available at https://huggingface.co/mradermacher/Apollo-1-4B-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 | imatrix | 0.1 | imatrix file (for creating your own qwuants) |
| GGUF | i1-IQ1_S | 1.2 | for the desperate |
| GGUF | i1-IQ1_M | 1.2 | mostly desperate |
| GGUF | i1-IQ2_XXS | 1.3 | |
| GGUF | i1-IQ2_XS | 1.5 | |
| GGUF | i1-IQ2_S | 1.5 | |
| GGUF | i1-IQ2_M | 1.6 | |
| GGUF | i1-Q2_K_S | 1.7 | very low quality |
| GGUF | i1-Q2_K | 1.8 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 1.8 | lower quality |
| GGUF | i1-IQ3_XS | 1.9 | |
| GGUF | i1-Q3_K_S | 2.0 | IQ3_XS probably better |
| GGUF | i1-IQ3_S | 2.0 | beats Q3_K* |
| GGUF | i1-IQ3_M | 2.1 | |
| GGUF | i1-Q3_K_M | 2.2 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 2.3 | IQ3_M probably better |
| GGUF | i1-IQ4_XS | 2.4 | |
| GGUF | i1-Q4_0 | 2.5 | fast, low quality |
| GGUF | i1-IQ4_NL | 2.5 | prefer IQ4_XS |
| GGUF | i1-Q4_K_S | 2.5 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 2.6 | fast, recommended |
| GGUF | i1-Q4_1 | 2.7 | |
| GGUF | i1-Q5_K_S | 2.9 | |
| GGUF | i1-Q5_K_M | 3.0 | |
| GGUF | i1-Q6_K | 3.4 | practically like static Q6_K |
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. Additional thanks to @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.