File size: 3,688 Bytes
fa0ee1d e5fa04c fa0ee1d d4caa30 fa0ee1d 5806294 fa0ee1d 5806294 fa0ee1d 61448a3 fa0ee1d a110ab6 d4caa30 fa0ee1d e5fa04c fa0ee1d |
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 74 |
---
base_model: nicolasdec/CabraQwen14b
language:
- pt
- en
library_name: transformers
license: cc
quantized_by: mradermacher
tags:
- text-generation-inference
- transformers
- qwen
- gguf
- brazil
- brasil
- 14b
- portuguese
---
## About
static quants of https://huggingface.co/nicolasdec/CabraQwen14b
<!-- 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/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q2_K.gguf) | Q2_K | 6.9 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.IQ3_XS.gguf) | IQ3_XS | 7.5 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.IQ3_S.gguf) | IQ3_S | 7.8 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q3_K_S.gguf) | Q3_K_S | 7.8 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.IQ3_M.gguf) | IQ3_M | 8.1 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q3_K_M.gguf) | Q3_K_M | 8.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q3_K_L.gguf) | Q3_K_L | 8.9 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.IQ4_XS.gguf) | IQ4_XS | 8.9 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q4_0.gguf) | Q4_0 | 9.2 | fast, low quality |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.IQ4_NL.gguf) | IQ4_NL | 9.3 | prefer IQ4_XS |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q4_K_S.gguf) | Q4_K_S | 9.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q4_K_M.gguf) | Q4_K_M | 10.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q5_K_S.gguf) | Q5_K_S | 11.0 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q5_K_M.gguf) | Q5_K_M | 11.5 | |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q6_K.gguf) | Q6_K | 13.3 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/CabraQwen14b-GGUF/resolve/main/CabraQwen14b.Q8_0.gguf) | Q8_0 | 15.9 | 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 -->
|