mradermacher's picture
auto-patch README.md
c7294dd verified
|
raw
history blame
5.47 kB
---
base_model: huihui-ai/aya-expanse-32b-abliterated
extra_gated_fields:
Affiliation: text
Country: country
I agree to use this model for non-commercial use ONLY: checkbox
Name: text
extra_gated_prompt: By submitting this form, you agree to the [License Agreement](https://cohere.com/c4ai-cc-by-nc-license) and
acknowledge that the information you provide will be collected, used, and shared
in accordance with Cohere’s [Privacy Policy]( https://cohere.com/privacy). You’ll
receive email updates about C4AI and Cohere research, events, products and services.
You can unsubscribe at any time.
language:
- en
- fr
- de
- es
- it
- pt
- ja
- ko
- zh
- ar
- el
- fa
- pl
- id
- cs
- he
- hi
- nl
- ro
- ru
- tr
- uk
- vi
library_name: transformers
license: cc-by-nc-4.0
quantized_by: mradermacher
tags:
- abliterated
- uncensored
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: nicoboss -->
weighted/imatrix quants of https://huggingface.co/huihui-ai/aya-expanse-32b-abliterated
<!-- provided-files -->
static quants are available at https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-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 |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ1_M.gguf) | i1-IQ1_M | 8.5 | mostly desperate |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 9.5 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ2_XS.gguf) | i1-IQ2_XS | 10.4 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ2_S.gguf) | i1-IQ2_S | 10.9 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ2_M.gguf) | i1-IQ2_M | 11.7 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q2_K_S.gguf) | i1-Q2_K_S | 12.1 | very low quality |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q2_K.gguf) | i1-Q2_K | 12.9 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 13.1 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q3_K_S.gguf) | i1-Q3_K_S | 14.8 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ3_M.gguf) | i1-IQ3_M | 15.3 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q3_K_M.gguf) | i1-Q3_K_M | 16.3 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q3_K_L.gguf) | i1-Q3_K_L | 17.7 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-IQ4_XS.gguf) | i1-IQ4_XS | 17.9 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q4_K_S.gguf) | i1-Q4_K_S | 18.9 | optimal size/speed/quality |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q4_K_M.gguf) | i1-Q4_K_M | 19.9 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q5_K_S.gguf) | i1-Q5_K_S | 22.6 | |
| [GGUF](https://huggingface.co/mradermacher/aya-expanse-32b-abliterated-i1-GGUF/resolve/main/aya-expanse-32b-abliterated.i1-Q6_K.gguf) | i1-Q6_K | 26.6 | practically like static Q6_K |
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. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
<!-- end -->