base_model: Sao10K/Fimbulvetr-10.7B-v1
language:
- en
library_name: transformers
license: cc-by-nc-4.0
quantized_by: mradermacher
About
static quants of https://huggingface.co/Sao10K/Fimbulvetr-10.7B-v1
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Fimbulvetr-10.7B-v1-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 | 4.3 | |
GGUF | IQ3_XS | 4.7 | |
GGUF | Q3_K_S | 4.9 | |
GGUF | IQ3_S | 4.9 | beats Q3_K* |
GGUF | IQ3_M | 5.1 | |
GGUF | Q3_K_M | 5.5 | lower quality |
GGUF | Q3_K_L | 5.9 | |
GGUF | IQ4_XS | 6.1 | |
GGUF | Q4_K_S | 6.4 | fast, recommended |
GGUF | Q4_K_M | 6.7 | fast, recommended |
GGUF | Q5_K_S | 7.7 | |
GGUF | Q5_K_M | 7.9 | |
GGUF | Q6_K | 9.1 | very good quality |
GGUF | Q8_0 | 11.6 | 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.