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---
base_model: open-neo/Kyro-n1.1-7B-pytorch
language:
- en
- zh
- fr
- es
- pt
- de
- it
- ru
- ja
- ko
- vi
- th
- ar
- fa
- he
- tr
- cs
- pl
- hi
- bn
- ur
- id
- ms
- lo
- my
- ceb
- km
- tl
- nl
library_name: transformers
license: other
license_link: LICENSE.md
license_name: kyro
quantized_by: mradermacher
tags:
- reasoning
- kyro
- open-neo
- open-source
- deepseek-r1
---
## About
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static quants of https://huggingface.co/open-neo/Kyro-n1.1-7B-pytorch
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weighted/imatrix quants are available at https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-i1-GGUF
## 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/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q2_K.gguf) | Q2_K | 3.1 | |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/Kyro-n1.1-7B-pytorch-GGUF/resolve/main/Kyro-n1.1-7B-pytorch.f16.gguf) | f16 | 15.3 | 16 bpw, overkill |
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](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/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.
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