File size: 3,501 Bytes
05f1f0b
86094de
05f1f0b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
6b8f513
05f1f0b
 
6f7112c
05f1f0b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
88beb7d
05f1f0b
 
 
e006030
88beb7d
 
05f1f0b
 
 
 
 
 
 
 
 
 
 
 
 
86094de
 
 
 
 
05f1f0b
 
 
 
 
 
 
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
---
base_model: maldv/SHRDFU-7b-gamma
datasets:
- maldv/crabcanon
language:
- en
library_name: transformers
license: cc-by-nc-4.0
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- GEB
---
## About

static quants of https://huggingface.co/maldv/SHRDFU-7b-gamma

<!-- provided-files -->
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/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q2_K.gguf) | Q2_K | 3.0 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.IQ3_XS.gguf) | IQ3_XS | 3.3 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q3_K_S.gguf) | Q3_K_S | 3.4 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.IQ3_S.gguf) | IQ3_S | 3.4 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.IQ3_M.gguf) | IQ3_M | 3.5 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q3_K_M.gguf) | Q3_K_M | 3.8 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q3_K_L.gguf) | Q3_K_L | 4.1 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.IQ4_XS.gguf) | IQ4_XS | 4.2 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q4_K_S.gguf) | Q4_K_S | 4.4 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q4_K_M.gguf) | Q4_K_M | 4.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q5_K_S.gguf) | Q5_K_S | 5.3 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q5_K_M.gguf) | Q5_K_M | 5.4 |  |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q6_K.gguf) | Q6_K | 6.2 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/SHRDFU-7b-gamma-GGUF/resolve/main/SHRDFU-7b-gamma.Q8_0.gguf) | Q8_0 | 7.9 | 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.

<!-- end -->