mradermacher/Ling-flash-base-2.0-i1-GGUF

About

weighted/imatrix quants of https://huggingface.co/inclusionAI/Ling-flash-base-2.0

For a convenient overview and download list, visit our model page for this model.

static quants are available at https://huggingface.co/mradermacher/Ling-flash-base-2.0-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	imatrix	0.4	imatrix file (for creating your own quants)
GGUF	i1-Q2_K	39.0	IQ3_XXS probably better
GGUF	i1-IQ3_XXS	41.1	lower quality
GGUF	i1-IQ3_XS	43.7
GGUF	i1-IQ3_S	46.1	beats Q3_K*
GGUF	i1-Q3_K_S	46.1	IQ3_XS probably better
GGUF	i1-IQ3_M	46.7
PART 1 PART 2	i1-Q3_K_M	51.0	IQ3_S probably better
PART 1 PART 2	i1-Q3_K_L	55.2	IQ3_M probably better
PART 1 PART 2	i1-IQ4_XS	56.8
PART 1 PART 2	i1-Q4_0	60.3	fast, low quality
PART 1 PART 2	i1-Q4_K_S	60.5	optimal size/speed/quality
PART 1 PART 2	i1-Q4_K_M	64.7	fast, recommended
PART 1 PART 2	i1-Q4_1	66.7
PART 1 PART 2	i1-Q5_K_S	73.3
PART 1 PART 2	i1-Q5_K_M	75.7
PART 1 PART 2	i1-Q6_K	87.3	practically like static Q6_K

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.