---
base_model: altomek/CodeRosa-70B-AB1
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
tags:
- merge
---
## About

static quants of https://huggingface.co/altomek/CodeRosa-70B-AB1

**altomek (creator of this model) thinks GGUF versions
of his model are very bad compared to the original model
(especially on the emotional level). Exllama seems less affected,
but also not well, so you should use the original model before
forming an opinion. Also, check the original model page for
the recommended prompt format.**

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weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## 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/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q2_K.gguf) | Q2_K | 25.9 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.IQ3_XS.gguf) | IQ3_XS | 28.6 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.IQ3_S.gguf) | IQ3_S | 30.3 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q3_K_S.gguf) | Q3_K_S | 30.3 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.IQ3_M.gguf) | IQ3_M | 31.4 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q3_K_M.gguf) | Q3_K_M | 33.7 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q3_K_L.gguf) | Q3_K_L | 36.6 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.IQ4_XS.gguf) | IQ4_XS | 37.6 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q4_K_S.gguf) | Q4_K_S | 39.7 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q4_K_M.gguf) | Q4_K_M | 41.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q5_K_S.gguf) | Q5_K_S | 47.9 |  |
| [GGUF](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q5_K_M.gguf) | Q5_K_M | 49.2 |  |
| [PART 1](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q6_K.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q6_K.gguf.part2of2) | Q6_K | 57.0 | very good quality |
| [PART 1](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/CodeRosa-70B-AB1-GGUF/resolve/main/CodeRosa-70B-AB1.Q8_0.gguf.part2of2) | Q8_0 | 73.6 | 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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