File size: 4,833 Bytes
d7218ff f895caf d7218ff 5872de9 d7218ff b87b595 d7218ff 41dbfad d7218ff 41dbfad c0547cb a72e6c4 d7de725 9e92ba5 c520f41 d7de725 9e92ba5 c520f41 d7de725 1005f38 9e92ba5 952e615 c520f41 9e92ba5 952e615 aa53654 d7218ff 3b9f4be f895caf aa53654 d7218ff |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 |
---
base_model: wolfram/miqu-1-103b
language:
- en
- de
- fr
- es
- it
library_name: transformers
license: other
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About
weighted/imatrix quants of https://huggingface.co/wolfram/miqu-1-103b
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/miqu-1-103b-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/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ1_S.gguf) | i1-IQ1_S | 22.1 | for the desperate |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 27.7 | |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 30.8 | |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ2_S.gguf) | i1-IQ2_S | 32.3 | |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ2_M.gguf) | i1-IQ2_M | 35.1 | |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q2_K.gguf) | i1-Q2_K | 38.3 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 40.0 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 42.5 | |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 44.9 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ3_S.gguf) | i1-IQ3_S | 45.0 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ3_M.gguf) | i1-IQ3_M | 46.5 | |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q3_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q3_K_M.gguf.part2of2) | i1-Q3_K_M | 50.0 | IQ3_S probably better |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q3_K_L.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q3_K_L.gguf.part2of2) | i1-Q3_K_L | 54.5 | IQ3_M probably better |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q4_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q4_K_S.gguf.part2of2) | i1-Q4_K_S | 59.0 | optimal size/speed/quality |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q4_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q4_K_M.gguf.part2of2) | i1-Q4_K_M | 62.3 | fast, recommended |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q5_K_S.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q5_K_S.gguf.part2of2) | i1-Q5_K_S | 71.4 | |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q5_K_M.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q5_K_M.gguf.part2of2) | i1-Q5_K_M | 73.3 | |
| [PART 1](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-Q6_K.gguf.part2of2) | i1-Q6_K | 85.1 | practically like static Q6_K |
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.
<!-- end -->
|