About
static quants of https://huggingface.co/DisOOM/Qwen1.5-55B-Chat-Cut
weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen1.5-55B-Chat-Cut-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 |
---|---|---|---|
GGUF | Q2_K | 20.8 | |
GGUF | Q3_K_S | 24.2 | |
GGUF | Q3_K_M | 26.9 | lower quality |
GGUF | Q3_K_L | 29.4 | |
GGUF | IQ4_XS | 29.8 | |
GGUF | Q4_K_S | 31.5 | fast, recommended |
GGUF | Q4_K_M | 33.4 | fast, recommended |
GGUF | Q5_K_S | 38.0 | |
GGUF | Q5_K_M | 39.1 | |
GGUF | Q6_K | 45.1 | very good quality |
PART 1 PART 2 | Q8_0 | 58.4 | 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. 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.
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Model tree for mradermacher/Qwen1.5-55B-Chat-Cut-GGUF
Base model
DisOOM/Qwen1.5-55B-Chat-Cut