README.md

---
language:
- en
library_name: transformers
license: cc-by-nc-4.0
quantized_by: mradermacher
---
## About

weighted/imatrix quants of https://huggingface.co/Sao10K/Fimbulvetr-11B-v2
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## Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) 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](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ2_M.gguf) | i1-IQ2_M | 3.9 |  |
| [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 4.4 | fast, lower quality |
| [GGUF](https://huggingface.co/mradermacher/Fimbulvetr-11B-v2-i1-GGUF/resolve/main/Fimbulvetr-11B-v2.i1-IQ3_XS.gguf) | i1-IQ3_XS | 4.7 |  |


Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

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