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---
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
---
## About
weighted/imatrix quants of https://huggingface.co/sophosympatheia/Aurora-Nights-70B-v1.0
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## 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/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-IQ1_S.gguf) | i1-IQ1_S | 14.9 | |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 18.6 | |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-IQ2_XS.gguf) | i1-IQ2_XS | 20.7 | |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q2_K.gguf) | i1-Q2_K | 25.8 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 27.3 | fast, lower quality |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q3_K_XS.gguf) | i1-Q3_K_XS | 28.6 | |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q3_K_S.gguf) | i1-Q3_K_S | 30.2 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q3_K_M.gguf) | i1-Q3_K_M | 33.6 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q3_K_L.gguf) | i1-Q3_K_L | 36.5 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q4_K_S.gguf) | i1-Q4_K_S | 39.6 | almost as good as Q4_K_M |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q4_K_M.gguf) | i1-Q4_K_M | 41.7 | fast, medium quality |
| [GGUF](https://huggingface.co/mradermacher/Aurora-Nights-70B-v1.0-i1-GGUF/resolve/main/Aurora-Nights-70B-v1.0.i1-Q5_K_M.gguf) | i1-Q5_K_M | 49.1 | best weighted quant |
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
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