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
static quants are available at https://huggingface.co/mradermacher/lzlv-limarpv3-l2-70b-GGUF
Usage
If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs 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 | i1-IQ1_S | 15.0 | for the desperate |
| GGUF | i1-IQ2_XXS | 18.7 | |
| GGUF | i1-IQ2_XS | 20.8 | |
| GGUF | i1-Q2_K | 25.9 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 27.4 | lower quality |
| GGUF | i1-Q3_K_XS | 28.7 | |
| GGUF | i1-Q3_K_S | 30.3 | IQ3_XS probably better |
| GGUF | i1-Q3_K_M | 33.7 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 36.6 | IQ3_M probably better |
| GGUF | i1-Q4_K_S | 39.7 | optimal size/speed/quality |
| GGUF | i1-Q4_K_M | 41.8 | fast, recommended |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
Thanks
I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.