metadata
base_model:
- 152334H/miqu-1-70b-sf
- lizpreciatior/lzlv_70b_fp16_hf
language:
- en
library_name: transformers
quantized_by: mradermacher
tags:
- mergekit
- merge
About
static quants of https://huggingface.co/wolfram/miquliz-120b-v2.0
While other static and imatrix quants are available already, I wanted a wider selection of quants available for this model.
weighted/imatrix quants are available at https://huggingface.co/mradermacher/miquliz-120b-v2.0-i1-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 | Q2_K | 44.6 | |
| PART 1 PART 2 | Q3_K_XS | 49.3 | |
| PART 1 PART 2 | Q3_K_S | 52.2 | |
| PART 1 PART 2 | Q3_K_M | 58.2 | lower quality |
| PART 1 PART 2 | Q3_K_L | 63.4 | |
| PART 1 PART 2 | Q4_K_S | 68.7 | fast, medium quality |
| PART 1 PART 2 | IQ4_NL | 68.8 | fast, slightly worse than Q4_K_S |
| PART 1 PART 2 | Q4_K_M | 72.6 | fast, medium quality |
| PART 1 PART 2 | Q5_K_S | 83.2 | |
| PART 1 PART 2 | Q5_K_M | 85.4 | |
| PART 1 PART 2 PART 3 | Q6_K | 99.1 | very good quality |
| PART 1 PART 2 PART 3 | Q8_0 | 128.2 | fast, best quality |
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