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---
base_model: alchemonaut/QuartetAnemoi-70B-t0.0001
language:
- en
library_name: transformers
license: other
quantized_by: mradermacher
tags:
- merge
---
## About

<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type:  -->
<!-- ### tags:  -->
static quants of https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001

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weighted/imatrix quants are available at https://huggingface.co/mradermacher/QuartetAnemoi-70B-t0.0001-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 |
|:-----|:-----|--------:|:------|
| [PART 1](https://huggingface.co/mradermacher/QuartetAnemoi-70B-t0.0001-GGUF/resolve/main/QuartetAnemoi-70B-t0.0001.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/QuartetAnemoi-70B-t0.0001-GGUF/resolve/main/QuartetAnemoi-70B-t0.0001.Q8_0.gguf.part2of2) | Q8_0 | 73.4 | fast, best quality |

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

## 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.

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