metadata
language:
- en
library_name: transformers
license: llama2
quantized_by: mradermacher
tags:
- aurelian
- WinterGoddess
- frankenmerge
- 120b
- 32k
About
weighted/imatrix quants of https://huggingface.co/llmixer/BigAurelian-v0.5-120b-32k
static quants are available at https://huggingface.co/mradermacher/BigAurelian-v0.5-120b-32k-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-Q2_K | 43.7 | IQ3_XXS probably better |
| PART 1 PART 2 | i1-Q3_K_S | 51.1 | IQ3_XS probably better |
| PART 1 PART 2 | i1-Q3_K_M | 57.0 | IQ3_S probably better |
| PART 1 PART 2 | i1-Q3_K_L | 62.1 | IQ3_M probably better |
| PART 1 PART 2 | i1-Q4_K_S | 67.2 | optimal size/speed/quality |
| PART 1 PART 2 | i1-Q4_K_M | 71.0 | fast, medium quality |
| PART 1 PART 2 PART 3 | i1-Q6_K | 97.0 | practically like static Q6_K |
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