base_model: migtissera/Tess-3-Mixtral-8x22B
language:
- en
library_name: transformers
license: apache-2.0
no_imatrtix: >-
Missing importance matrix for tensor blk.29.ffn_down_exps.weight in a very
low-bit quantization
quantized_by: mradermacher
About
weighted/imatrix quants of https://huggingface.co/migtissera/Tess-3-Mixtral-8x22B
llama.cpp crashes when creating some of the imatrix quants. Only the ones where it did not crash will be provided. quality is likely reduced. When in doubt, compare with the static quants, which should be safe.
static quants are available at https://huggingface.co/mradermacher/Tess-3-Mixtral-8x22B-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 |
|---|---|---|---|
| PART 1 PART 2 | i1-Q2_K | 52.2 | IQ3_XXS probably better |
| PART 1 PART 2 | i1-IQ3_XXS | 55.0 | lower quality |
| PART 1 PART 2 | i1-IQ3_M | 64.6 | |
| PART 1 PART 2 | i1-Q3_K_M | 67.9 | IQ3_S probably better |
| PART 1 PART 2 | i1-Q4_K_S | 80.6 | optimal size/speed/quality |
| PART 1 PART 2 | i1-Q4_K_M | 85.7 | 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
FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
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. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.