metadata
base_model:
- 152334H/miqu-1-70b-sf
language:
- en
library_name: transformers
quantized_by: mradermacher
tags:
- mergekit
- merge
About
weighted/imatrix quants of https://huggingface.co/wolfram/miqu-1-103b
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 | 22.1 | |
| GGUF | i1-IQ2_XXS | 27.7 | |
| GGUF | i1-IQ2_XS | 30.8 | |
| GGUF | i1-IQ2_S | 32.3 | |
| GGUF | i1-IQ2_M | 35.1 | |
| GGUF | i1-IQ3_XXS | 40.0 | fast, lower quality |
| GGUF | i1-IQ3_XS | 42.5 | |
| GGUF | i1-IQ3_S | 45.0 | fast, beats Q3_K* |
| GGUF | i1-IQ3_M | 46.5 | |
| PART 1 PART 2 | i1-Q3_K_M | 50.0 | IQ3_S probably better |
| PART 1 PART 2 | i1-Q4_K_M | 62.3 | fast, medium 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