base_model, datasets, extra_gated_fields, extra_gated_prompt, language, library_name, license, quantized_by, tags

base_model	datasets	extra_gated_fields	extra_gated_prompt	language	library_name	license	quantized_by	tags
bigcode/starcoderbase	bigcode/the-stack-dedup	I accept the above license agreement, and will use the Model complying with the set of use restrictions and sharing requirements checkbox	## Model License Agreement Please read the BigCode [OpenRAIL-M license](https://huggingface.co/spaces/bigcode/bigcode-model-license-agreement) agreement before accepting it.	en	transformers	bigcode-openrail-m	mradermacher	code

About

static quants of https://huggingface.co/bigcode/starcoderbase

weighted/imatrix quants are available at https://huggingface.co/mradermacher/starcoderbase-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	6.4
GGUF	IQ3_XS	7.0
GGUF	IQ3_S	7.2	beats Q3_K*
GGUF	Q3_K_S	7.2
GGUF	IQ3_M	7.7
GGUF	Q3_K_M	8.5	lower quality
GGUF	IQ4_XS	8.9
GGUF	Q4_K_S	9.4	fast, recommended
GGUF	Q3_K_L	9.4
GGUF	Q4_K_M	10.2	fast, recommended
GGUF	Q5_K_S	11.2
GGUF	Q5_K_M	11.8
GGUF	Q6_K	13.2	very good quality
GGUF	Q8_0	17.1	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.