About
static quants of https://huggingface.co/ibivibiv/giant-hydra-moe-240b
weighted/imatrix quants are available at https://huggingface.co/mradermacher/giant-hydra-moe-240b-i1-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 | Q2_K | 87.6 | |
| PART 1 PART 2 | Q3_K_XS | 96.5 | |
| PART 1 PART 2 PART 3 | Q3_K_S | 103.5 | |
| PART 1 PART 2 PART 3 | Q3_K_M | 114.8 | lower quality |
| PART 1 PART 2 PART 3 | Q3_K_L | 124.3 | |
| PART 1 PART 2 PART 3 | Q4_K_S | 136.2 | fast, recommended |
| PART 1 PART 2 PART 3 | Q4_K_M | 144.8 | fast, recommended |
| PART 1 PART 2 PART 3 PART 4 | Q5_K_S | 164.7 | |
| PART 1 PART 2 PART 3 PART 4 | Q5_K_M | 169.7 | |
| P1 P2 P3 P4 P5 | Q6_K | 196.3 | very good quality |
| P1 P2 P3 P4 P5 P6 | Q8_0 | 253.9 | fast, best 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
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.
Model tree for mradermacher/giant-hydra-moe-240b-GGUF
Base model
ibivibiv/giant-hydra-moe-240b