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---
base_model:
- 152334H/miqu-1-70b-sf
language:
- en
library_name: transformers
quantized_by: mradermacher
tags:
- mergekit
- merge
---
## About
weighted/imatrix quants of https://huggingface.co/wolfram/miqu-1-103b
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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/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ2_M.gguf) | i1-IQ2_M | 35.0 | |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 39.9 | fast, lower quality |
| [GGUF](https://huggingface.co/mradermacher/miqu-1-103b-i1-GGUF/resolve/main/miqu-1-103b.i1-IQ3_XS.gguf) | i1-IQ3_XS | 42.4 | |
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
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