metadata
language:
- en
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
About
weighted/imatrix quants of https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1
Artefact2 also made some, with a different weight matrix, at https://huggingface.co/Artefact2/Mixtral-8x7B-Instruct-v0.1-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-IQ1_S | 9.7 | |
| GGUF | i1-IQ2_XXS | 12.5 | |
| GGUF | i1-IQ2_XS | 13.8 | |
| GGUF | i1-Q2_K | 17.5 | IQ3_XXS probably better |
| GGUF | i1-IQ3_XXS | 18.5 | fast, lower quality |
| GGUF | i1-Q3_K_XS | 19.2 | |
| GGUF | i1-Q3_K_S | 20.6 | IQ3_XS probably better |
| GGUF | i1-Q3_K_M | 22.7 | IQ3_S probably better |
| GGUF | i1-Q3_K_L | 24.3 | IQ3_M probably better |
| GGUF | i1-Q4_K_S | 26.9 | almost as good as Q4_K_M |
| GGUF | i1-Q4_K_M | 28.6 | fast, medium quality |
| GGUF | i1-Q5_K_M | 33.4 | best weighted quant |
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