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bazwyn/Aeshma-12B-imat-GGUF
Aeshma-12B-imat-GGUF is a machine learning model from bazwyn. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
113
11% of all-time downloads
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.gguf75.8 GB · 100%
From the Hugging Face model README

This is a TIES merger made and quanted in the shadows of some of the more popular releases.
I'm not sure it does anything better than anyone else, but when I started learning,
I said I would add more quants for a model I thought was good enough to deserve it.
I may be biased, but I think it's good, and I've used it quite frequently under its formal test name Stage8c-12B
I'm going to leave this here along with the bf16 and imatrix.dat so that people can make their own quants if they want. In the future I'll re-visit this if I don't get sidetracked learning new stuff, since I've spent far too long fine tuning a soup recipe.
If you are unsure how to use GGUF files See: TheBloke's READMEs
(sorted by file size, IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| GGUF | imat-IQ3_XS | 5.2 | |
| GGUF | imat-IQ4_XS | 6.6 | Optimal Size/Speed |
| GGUF | imat-Q4_K_M | 7.3 | |
| GGUF | imat-Q5_K_M | 8.5 | |
| GGUF | imat-6_K | 9.8 | |
| GGUF | imat-8_0 | 13 | |
| GGUF | BF16 | 24 | if you want to make static quants |
| DAT | imatrix | n/a | bf16+dat+llama-quantize, for other imat quants |
Here is a graph by ikawrakow comparing some lower-quality quant types (as borrowed from mradermacher, along with some of my layout):

The following YAML configuration was used to produce this model:
models:
- model: anthracite-org/magnum-v4-12b
parameters:
density: 0.82
weight: 0.4
- model: MarinaraSpaghetti/NemoMix-Unleashed-12B
parameters:
density: 0.69
weight: 0.25
- model: TheDrummer/Rocinante-12B-v1.1
parameters:
density: 0.69
weight: 0.35
merge_method: ties
base_model: nbeerbower/mistral-nemo-bophades-12B
parameters:
normalize: true
int8_mask: true
dtype: bfloat16