base_model: jukofyork/command-a-03-2025-uncut
datasets:
- jukofyork/instruction-refusals-500MB
- jukofyork/instruction-responses-500MB
language:
- en
- fr
- de
- es
- it
- pt
- ja
- ko
- zh
- ar
- el
- fa
- pl
- id
- cs
- he
- hi
- nl
- ro
- ru
- tr
- uk
- vi
library_name: transformers
license: cc-by-nc-4.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
About
static quants of https://huggingface.co/jukofyork/command-a-03-2025-uncut
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/command-a-03-2025-uncut-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 | 42.2 | |
| GGUF | Q3_K_S | 49.1 | |
| PART 1 PART 2 | Q3_K_M | 54.5 | lower quality |
| PART 1 PART 2 | Q3_K_L | 59.2 | |
| PART 1 PART 2 | IQ4_XS | 60.7 | |
| PART 1 PART 2 | Q4_K_S | 63.9 | fast, recommended |
| PART 1 PART 2 | Q4_K_M | 67.2 | fast, recommended |
| PART 1 PART 2 | Q5_K_S | 76.9 | |
| PART 1 PART 2 | Q5_K_M | 78.9 | |
| PART 1 PART 2 | Q6_K | 91.2 | very good quality |
| PART 1 PART 2 PART 3 | Q8_0 | 118.1 | 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, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.