File size: 2,717 Bytes
09917d3 e23e44c 09917d3 e23e44c 09917d3 3570c21 09917d3 3570c21 09917d3 3570c21 09917d3 aab7f02 09917d3 e9c8d12 09917d3 2575f85 09917d3 2575f85 09917d3 3570c21 91ce221 aab7f02 91ce221 aab7f02 f65f788 09917d3 |
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 |
---
language:
- en
library_name: transformers
quantized_by: mradermacher
tags:
- llama
- llama 2
---
## About
weighted/imatrix quants of https://huggingface.co/Doctor-Shotgun/lzlv-limarpv3-l2-70b
<!-- provided-files -->
## 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/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-IQ1_S.gguf) | i1-IQ1_S | 14.9 | |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 18.6 | |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-IQ2_XS.gguf) | i1-IQ2_XS | 20.7 | |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q2_K.gguf) | i1-Q2_K | 25.8 | IQ3_XXS probably better |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 27.3 | fast, lower quality |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q3_K_XS.gguf) | i1-Q3_K_XS | 28.6 | |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q3_K_S.gguf) | i1-Q3_K_S | 30.2 | IQ3_XS probably better |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q3_K_M.gguf) | i1-Q3_K_M | 33.6 | IQ3_S probably better |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q3_K_L.gguf) | i1-Q3_K_L | 36.5 | IQ3_M probably better |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q4_K_S.gguf) | i1-Q4_K_S | 39.6 | almost as good as Q4_K_M |
| [GGUF](https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-i1-GGUF/resolve/main/lzlv-limarpv3-l2-70b.i1-Q4_K_M.gguf) | i1-Q4_K_M | 41.7 | fast, medium 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
<!-- end -->
|