base_model: mpasila/Viking-SlimInstruct-V1-7B
datasets:
- mpasila/Viking-Instruct-Mix
- saillab/alpaca-icelandic-cleaned
- kobprof/skolegpt-instruct
- tollefj/nor-instruct-cleaned
- skvarre/sv-instruct-v1
- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned-20k
- LumiOpen/instruction-collection-fin
- neph1/Alpaca-Lora-GPT4-Swedish-Refined
language:
- en
- fi
- 'no'
- nb
- da
- sv
- is
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
- unsloth
- trl
- sft
About
weighted/imatrix quants of https://huggingface.co/mpasila/Viking-SlimInstruct-V1-7B
static quants are available at https://huggingface.co/mradermacher/Viking-SlimInstruct-V1-7B-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 | i1-Q2_K | 3.1 | IQ3_XXS probably better |
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.